USOO9134398B2

(12) United States Patent (10) Patent No.: US 9,134,398 B2 Dupray et al. (45) Date of Patent: Sep. 15, 2015

(54) WIRELESS LOCATION USING NETWORK (56) References Cited CENTRC LOCATION ESTMLATORS U.S. PATENT DOCUMENTS (75) Inventors: Dennis J. Dupray, Golden, CO (US); M Charles L. Karr, Tuscaloosa, AL (US); 3,630,079 A 12/1971 Hughes et al. Sheldon F. Goldberg, Las Vegas, NV 3,646,580 A 2f1972 Fuller et al. (US) (Continued) (73) Assignee: TracBeam LLC, Golden, CO (US) FOREIGN PATENT DOCUMENTS (*) Notice: Subject to any disclaimer, the term of this patent is extended or adjusted under 35 EP O1772O3 4f1986 U.S.C. 154(b) by 0 days. EP O346461 12/1989 (21) Appl. No.: 13/323,221 (Continued) (22) Filed: Dec. 12, 2011 OTHER PUBLICATIONS O O Defendants' Motion for Partial Summary Judgment of Invalidity (65) Prior Publication Data Based on Indefiniteness filed in the United States District Court for the Eastern District of Texas, Tyler Division, at Case No. 6: 11-cv US 2012/O190380 A1 Jul. 26, 2012 00096-LED, on Sep. 25, 2012, 22 pages. (Continued) Related U.S. Application Data Primary Examiner — Dao Phan (63) Continuation-in-part of application No. 1 1/739,097, (74) Attorney, Agent, or Firm — Dennis J. Dupray filed on Apr. 24, 2007, which is a continuation of y y application No. 09/194,367, filed as application No. (57) ABSTRACT PCT/US97/15892 on Sep. 8, 1997, now Pat. No. A wireless location system is disclosed- 0 having one or more (Continued) location centers for locating mobile stations (MS) based on, e.g., WIFI, CDMA, AMPS, NAMPS, TDMA, GPRS, and (51) Int. Cl. GSM. MS location requestsC can be pprocessed via,1a, e.g.,e.g Inter GOIS I/02 (2010.01) net communication between a network of location centers. A GOIS5/00 2OO 6. O1 plurality of MS locating technologies may be used, including ( .01) those based on: two-way TOA and TDOA: pattern recogni (Continued) tion; distributed antennas; and reduced coverage base sta (52) U.S. Cl tions. The system includes strategies for: automatically AV e. we adapting and calibrating system performance according to CPC (2013.01). SE (OS28 E. environmental and geographical changes; automatically cap ( .01): ( .01): turing location signal data for enhancing a historical database (2013.01); retaining predictive location signal data; evaluating MS loca (Continued) tions according to heuristics and constraints related to, e.g., (58) Field of Classification Search terrain, MS velocity and path; and adjusting likely MS loca tions adaptively and statistically. The system is useful for CPC ...... G01S 5/06; G01S 5/0221; G01S 5/0252: emergency calls, tracking, routing, people and animal loca tion including applications for confinement to and exclusion USPC ...... 342/357.73, 450, 453, 457, 465, 451, from certain areas. 342/463; 455/4.56.1, 456.3, 456.6 See application file for complete search history. 37 Claims, 62 Drawing Sheets

is LOCATION NFORMATION DATABASES e is

SWITCHING CENTER112 HYPOTHESISEALUATOR 1228 's "MOSTLIKELY"Location HYPOTHESISDETERMINATION ERRORRENTALDATAPROVIDERS E.g. APPLICATIONS PROVIDING TRAFFICFlow, ETWORK 124 i-R oUTPUTGATEWAY WEATHER, Etc. ARINTERFET FoRDESIGNATED 468 EvoNENTALDATABASEs LOCATION LOCATION APPLICATIONS146 sc. APPictions35 US 9,134,398 B2 Page 2

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LED by the United States District Court for the Eastern District of PlaintiffTracBeam's Second Supplemental Response to Defendants' Texas, Tyler Division, on Jan. 23, 2013, 39 pages. Common Interrogatory Nos. 2 filed in Case Nos. 6: 11-cv-00096 Official Action for U.S. Appl. No. 1 1/739,097, mailed Apr. 3, 2013. LED and 6:13-cv-00093-LED, U.S. District Court for the Eastern U.S. Appl. No. 13/831,674, filed Mar. 15, 2013, Dupray et al. District of Texas, Tyler Division, May 21, 2013, 25 pages. U.S. Appl. No. 13/844,708, filed Mar. 15, 2013, Dupray et al. Report of William Michelson, Ph.D., Concerning Validity of Claims U.S. Appl. No. 13/843,204, filed Mar. 15, 2013, LeBlanc et al. 1, 7, 25, 106, and 215 of U.S. Pat. No. 7,764,231 and Claims 51, 56, U.S. Appl. No. 13/844,500, filed Mar. 15, 2013, Dupray et al. and 67 of U.S. Pat. No. 7,525,484 dated May 24, 2013, 379 pages. “GPS Interface Control Document ICD-GPS-200. IRN-200B Expert Report of the Honorable Gerald J. Mossinghoff dated May 24, PR001, Jul. 1, 1992 revision, reprinted Feb. 1995, 109 pages. 2013, 32 pages. Beser, J. and B.W. Parkinson, “The Application of NAVSTAR Dif Supplemental Report of William Michelson, Ph.D., Concerning the ferential GPS in the Civilian Community.” Navigation: Journal of the Invalidity of U.S. Pat. No. 7,764,231 and U.S. Pat. No. 7,525,484 for Institute of Navigation, Summer 1982, vol. 29(2), pp. 107-136. Improper Inventorship dated Jun. 7, 2013, 13 pages. Boucher, Neil J., “Cellular Radio Handbook.” Quantum Publishing, Supplemental Expert Report of Michael S. Braasch Regarding Inval 1990, 91 pages. idity of Asserted Claims of U.S. Pat. No. 7,764,231 and U.S. Pat. No. Frank, R.L., “Current Developments in Loran-C.” Proceedings of the 7.525,484 for Improper Inventorship dated Jun. 7, 2013, 31 pages. IEEE, Oct. 1983, vol. 71(10), pp. 1127-1142. Deposition of Dennis Dupray held in Case Nos. 6: 11-cv-00096-LED Giordano et al., “A Novel Location Based Service and Architecture.” and 6:13-cv-00093-LED. U.S. District Court for the Eastern District IEEE PIMRC '95, Sep. 1995, vol. 2, pp. 853-857. of Texas, Tyler Division, Feb. 20, 2013, 225 pages. Giordano et al., “Location Enhanced Cellular Information Services.” Deposition of Charles Karr held in Case No. 6: 11-cv-00096-LED. 5th IEEE International Symposium on Personal, Indoor and Mobile U.S. District Court for the Eastern District of Texas, Marshall Divi Radio Communications, Sep. 18-23, 1994, pp. 1143-1145. sion, Mar. 12, 2013, 243 pages. Kaplan, E., “Understanding GPS: Principles and Applications.” Official Action for U.S. Appl. No. 1 1/739,097, mailed Sep. 30, 2013. Artech House, 1996, 288 pages. Official Action for U.S. Appl. No. 12/786,429, mailed Nov. 27, 2013. US 9,134,398 B2 Page 13

(56) References Cited for the Eastern District of Texas, Tyler Division, Feb. 21, 2013, 100 pageS. OTHER PUBLICATIONS Deposition of Dennis Dupray (Redacted vol. III) held in Case Nos. 6:11-cv-00096-LED and 6:13-cv-00093-LED, U.S. District Court Official Action (Restriction Requirement) for U.S. Appl. No. for the Eastern District of Texas, Tyler Division, Feb. 22, 2013, 43 13/831,674, mailed Nov. 19, 2013. pageS. Notice of Allowance for U.S. Appl. No. 12/786,429, mailed Jul. 30, Deposition of Dennis Dupray (Redacted vol. IV) held in Case Nos. 2014. 6:11-cv-00096-LED and 6:13-cv-00093-LED, U.S. District Court Official Action for U.S. Appl. No. 1 1/739,097, mailed Oct. 22, 2014. for the Eastern District of Texas, Tyler Division, May 29, 2013, 50 Deposition of Frederick Warren LeBlanc (Redacted) held in Case No. pageS. 6:11-cv-00096-LED, U.S. District Court for the Eastern District of Deposition of Dennis Dupray (Redacted vol. V) held in Case Nos. Texas, Marshall Division, Mar. 13, 2013, 125 pages. 6:11-cv-00096-LED and 6:13-cv-00093-LED, U.S. District Court Deposition of Dennis Dupray (Redacted vol. I) held in Case Nos. for the Eastern District of Texas, Tyler Division, Aug. 19, 2013, 66 6:11-cv-00096-LED and 6:13-cv-00093-LED, U.S. District Court pageS. for the Eastern District of Texas, Tyler Division, Feb. 20, 2013, 225 Deposition of Corey K. Ford held in Case No. 6:13-CV-93-LED. U.S. pageS. District Court for the Eastern District of Texas, Marshall Division, Deposition of Dennis Dupray (Redacted vol. II) held in Case Nos. Apr. 16, 2013, 68 pages. 6:11-cv-00096-LED and 6:13-cv-00093-LED, U.S. District Court Official Action for U.S. Appl. No. 13/831,674, mailed Apr. 3, 2014. U.S. Patent Sep. 15, 2015 Sheet 1 of 62 US 9,134,398 B2

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U.S. Patent Sep. 15, 2015 Sheet 2 of 62 US 9,134,398 B2 U.S. Patent US 9,134,398 B2

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U.S. Patent Sep. 15, 2015 Sheet 4 of 62 US 9,134,398 B2

U.S. Patent Sep. 15, 2015 Sheet 6 of 62 US 9,134,398 B2

Fig. 6(1) LOCATION CENTER 142 SIGNAL PROCESSING 1220 SUBSYSTEM VERIFED LOCATION SIGNATURE

1, SGNAL FILTERING AND INPUT LOCATION FIRST ORDER LOCATION MODELS 1224 DATASTRUCTURE (INCLUDES DISTINCTMS LOCATION CREATION MODELS THAT OUTPUT LOCATION HYPOTHESES) LOCATION CENTER CONTROL SUBSYSTEM

SUPERVISOR 1 CONTROLS LOCATION ESTIMATION SYSTEM 2. DETERMINES CONTEXT OR STATE OF LOCATION PERFORMANCE DATA BASE PROBLEM; E.G., FIRST 1DATA HERE IS USED WITH THE OR SECOND SET OF "...r.| ADAPTATION ENGINE (EG, FORTUNING MEASUREMENTS FOR THE CONTEXT ADJUSTER). 3.DETERMINES APPROPRIATE REPLIES TOBSs: 4. NOTES"HEALTH" OF BS MEASUREMENTS : ADAPTATION ENGINE

: 1...BACKGROUND PROCESS TO ADAPTIVELY TUNE THE LOCATION ENGINE 139; i. OPERATOR 2. USES STORED DATA TO ADJUST SYSTEM PARAMETERS ACCORDING TO PAST PERFORMANCES; 3.GENERAL PURPOSE, USES NO DOMAINKNOWLEDGE

1356 PUBLIC OUTPUTGATEWAY (TODESIGNATED

TELEPHONE LOCATIONAPPLICATIONS) H SWITCHING 1DETERMINES THE APPLICATIONS NYSE: RECEIVING OUTPUT AND THE MSC 12SMS FREQUENCY OF OUTPUT TO EACH 105, and SCP 104 APPLICATION U.S. Patent Sep. 15, 2015 Sheet 7 of 62 US 9,134,398 B2

FIG 6(2) LOCATION CENTER 142 LOCATION ENGINE 139 - NEURALNET TRAINING DATA BASE

ENVIRONMENTALDATA BASE AREA CHARACTERISTICS 1354 DATA BASE 1450 1STORESCURRENTTRAFFICETC CONDITIONS WEATHER, |- -

2. USED BY CONTEXT ADJUSTER PATHWAY DATA BASE 1326, ANALYTICAL REASONER

1416 & MAYBE FOMS. 1224

HYPOTHESIS EVALUATOR 228 CONTEXT ADJUSTER 1326 1ADJUSTS THE CONFIDENCE AND/OR AREA FIELDS OF LOCATION HYPOTHESES OUTPUT BY FIRST ORDERMODELS TO OBTAIN MORE RELIABLE TARGETMS ESTMATES USING VERIFED LOCATION SIGNATURE CLUSTERS INTHE LOCATION SIGNATURE DATABASE. 2.IN ONE EMBODIMENT, THIS MODULE MODIFIES A TARGET MSLOCATION IN RELATION TO VARIOUS ENVIRONMENTAL CHARACTERISTICS SUCH AS: THE GEOGRAPHICAL AREA (TYPE) ASSOCATED WITHALOCATION HYPOTHESIS, WEATHER, TIME OF DAY, SEASON, TRAFFIC, ETC; 3. IN ONEEMBODIMENT, MAYUSE HEURISTIC (FUZZY LOGIC) RULES TO ADJUST THE CONFIDENCEVALUES: 4. IN ONE EMBODIMENT, MAYALSOUSE EXPERT SYSTEM RULES FOR ADJUSTING CONFIDENCESDUETOBS ES 5. FORLBSs (FIXEDLOCATIONTRANSCEIVERS), MAYUSE OUTPUT FROM THE FIRST ORDERMODELS FOR SUCH TRANSCEIVERS AS AWAY TO CALIBRATE LOCATION HYPOTHESIS DEFAULT CONFIDENCEVALUES OF OTHER FOMs. LOCATION HYPESIS ANALYZER LOCATIONESTIMATOR (INCLUDESBLACKBOARD AND/OR 1. RECEIVES RESULTING EXPERT SYSTEM) Forests (WITH MS STATUS REPOSITORY (RUN-TIME TRACKING) HIGHEST 1, RUN-TIME STORAGE FOR PREVIOUS TARGETMS CONFIDENCES) AND PATHORTRACKING DATA, E.G., PREVIOUS Kit NETS foot'EUT | IARGETMSOCATIONHYPOTHESES & LOCATION A SINGLE (SET OF PREDICTIONS FOR RECENTLY LOCATED MSs. E.G., NESTED) AREA(S MS PATHS MAYBE STORED HERE FOR USE IN WITH PROBABILITIES EXTRAPOLATING ANEWMS LOCATIONESTMATE. ASSOCATED WITH 2. LOG CONTEXT OR STATE OF A TARGET MS EACH AREA LOCATION PROBLEM, EG, FIRST OR SECONDSET OF MEASUREMENTS FOR TARGETMS U.S. Patent Sep. 15, 2015 Sheet 8 of 62 US 9,134,398 B2

FIG 6(3)

LOCATION CENTER 142 LOCATION ENGINE 139

LOCATIONSIGNATURE DATA BASE 1STORES CDMA SIGNAL CHARACTERISTICS FORVERIFED LOCATIONS (E.G., LOCATIONSIGNATURES OR LOCSIGS); 2. EACH LOC SIGALLOWSACCESS TO: MSLAT-LONG, BSD, POWER LEVELS (BSANDMS), TIMEIDATESTAMP, ENVIRONMENTAL MEASUREMENTS INDICATING, E.G., RF BACKGROUND NOISE, MULTIPATH, DENSE URBAN, URBAN, SUBURBAN, RURAL MOUNTAIN, WEATHER, TRAFFIC, AND A CONFIDENCEVALUE FOR THE LOCSIG. 3. SUPPORTED RETRIEVALS: BY GEOGRAPHICAL AREA, BY BSID, BY ENVIRONMENTAL MEASUREMENT CLASSIFICATIONS, BY TIME/DATE RANGE. 4. LOC SGS INPUT FROM 2 SOURCES: FIXEDLOCATION MSS (E.G., LBS'S, 12 LOC SIGS/LBS/DAY FOR A YEAR), OTHER VERIFED SOURCES PROVIDED BY A MBS 148 OR ANOTHER UNIT HAVING LOCATION VERIFICATION FUNCTIONALITY, E.G., POLICE, AMBULANCES, BUSES, TAXIS

U.S. Patent Sep. 15, 2015 Sheet 11 of 62 US 9,134,398 B2

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U.S. Patent Sep. 15, 2015 Sheet 23 of 62 US 9,134,398 B2 U.S. Patent Sep. 15, 2015 Sheet 24 of 62 US 9,134,398 B2 U.S. Patent Sep. 15, 2015 Sheet 25 of 62 US 9,134,398 B2

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IS "NEW LOC OBJ" IN THE LOCATION SIGNATURE DATA BASE 104 DB

INSERT "NEW LOC OBJ" IN THE LOCATION SIGNATURE DATA BASE 1320.

DB SEARCH AREA-- GET A REPRESENTATION OF A GEOGRAPHICA, AREA SURROUNDING THE LOCATION ASSOCATED WITH "NEW LOC OBJ".

112 DB DB LOC SIGS--GET ALL THE LOCSIGS IN THE LOCATION SIGNATURE DATA BASE THAT SATISFY THE CRITERIA OF "SELECTION CRITERIA" AND THAT ARE 116 DB ALSO IN "DB SEARCH AREA1".

NEARBY LOC SIG BAG - GET THE LOCSIGS FROM "DB LOC SIGS", WHEREIN FOREACH LOCSIG GOTTEN, THE DISTANCE BETWEEN THE LOCATIONASSOCATED WITH THE LOC SG GOTTEN AND THE LOCATIONASSOCATED WITH "NEW LOC OBJ" IS CLOSER THAN, E.G., SOME STANDARD DEVIATION (SUCH ASA SECOND STANDARD DEVIATION) OF THE DISTANCES BETWEEN LOCSIGS OF "DB LOC SIGS" AND "NEW LOC OBJ".

LOC SIG--GET THE FIRST (NEXT) LOCSIG IN "NEARBY LOC SIG BAG".

120 DB FIG. 17A U.S. Patent Sep. 15, 2015 Sheet 27 of 62 US 9,134,398 B2

124 DB LOC-I-A REPRESENTATION OF THE LOCATIONASSOCIATED WITH

"LOC SIG". 128 DB

BS-GET THE BASE STATION 122 ASSOCATED WITH "LOC SIG".

132 DB MARK"LOC SIG" SO THAT IT CANNOT BE RETRIEVED FROM THE LOCATION SIGNATURE DATA BASE.

136 DB DB SEARCH AREA2- GET A REPRESENTATION OF A GEOGRAPHICAL SERVICE AREA ABOUT LOC SIG

INCLUDING "NEW LOC OBJ". 138 OB LOC SIG BAG-e-CREATE LOCSIG BAG DATASTRUCTURE HAVING ONLY THE SINGLE ITEM, "LOC SIG".

INVOKE THE PROGRAM, "DETERMINE LOCATION SIGNATURE FIT ERRORS", FOR DETERMINING AN ERROR IN HOWSIMILAR"LOC SIG" IS WITH OTHERVERIFIED LOC SIGS IN THE LOCATION SIGNATURE DATA BASE. IN PARTICULAR, INVOKE THIS PROGRAM WITH THE FOLLOWING PARAMETERS: (A) "LOC"; (B) "LOC SIG BAG"; (C) "DB SEARCH AREA2"; (D)"LOC SIG POP" FOR INDICATING THE VERIFIED LOC SIGS IN THE LOCATION SIGNATURE DATA BASE TO WHICH "LOC SIG" IS TO BE COMPARED, (E) AN INDICATION OF THE OUTPUT DESIRED, WHICH, IN THIS CASE, IS AN ERROR RECORD RELATED TO "LOC SIG".

140 DB UNMARK"LOC SIG"SO THAT IT CAN BE FIG. 17B RETRIEVED FROM THE LOCATION SIGNATURE DATA BASE.

144 DB U.S. Patent Sep. 15, 2015 Sheet 28 of 62 US 9,134,398 B2

IS THERE ANOTHER LOC SIG N"NEARBY LOC SIG BAG"? YES I - - -

148 DB NO 152 DB

ERROR REC SET --THE SET OF ALL ERRORS RETURNED.

INVOKE THE PROGRAM, "REDUCE BAD DB LOC SIGS", FOR REDUCING THE CONFIDENCE OF THE LOCSIGS WHOSE CORRESPONDINGERRORS ARE RELATIVELY HIGH ALSO, DELETE ANY LOCSIG WHOSE CONFIDENCE BECOMES TOO LOW.

156 DB

INVOKE THE PROGRAM, "INCREASE CONFIDENCE OF GOOD DB LOC SIGS", FOR INCREASING THE CONFIDENCE OF THE LOCSIGS WHOSE CORRESPONDINGERRORS ARE RELATIVELY LOW.

END 160 DB

FIG. 17C U.S. Patent Sep. 15, 2015 Sheet 29 of 62 US 9,134,398 B2

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U.S. Patent Sep. 15, 2015 Sheet 32 of 62 US 9,134,398 B2

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U.S. Patent Sep. 15, 2015 Sheet 37 of 62 US 9,134,398 B2

APPLY PRE-PROCESING CONSTRAINTS TO ACCOUNT FOR DISCREPANCIES BETWEEN (a) CURRENT CONDITIONS, AND (b) PAST CONDITIONS WHEN THE VERIFIED LOCSIGS OF "LOC SIG BAG" WERE COLLECTED, i.e., APPLY CONSTRAINTS TO TAKE INTO ACCONT ADDITIONAL KNOWLEDGE REGARDING DISTINCTIONS BETWEEN THE CONDITIONS RELATED TO THE PRESENT WIRELESS ENVIRONMENT, TYPE AND STATUS OF THE BASE STATION OF "BS" IN COMPARISON TO THE CONDITIONS OCCURRING FOR THE LOC SIGS OF "LOC SIG BAG"

DD THE PRE-PROCESSING CONSTRAINTS YIELD A RESULT INDICATING THAT ANY SUBSEQUENTLY DERIVED LOCSIG ESTIMATE WOULD BE EXCESSIVELY UNRELIABLE C YES NO FOREACH OF THE LOC SIG SIGNAL TOPOGRAPHY CHARACTERISTICS, C, OF A LOC SIG VARIABLE, "EST LOC SIG", RETURN (A) DETERMINE A SMOOTH SURFACE, S(C), OF MINIMAL CONTOUR VARATION FOR THE SET OF POINTS {(X,Y,Z) SUCH THAT (X,Y) ISA LOCATION AND Z IS A VALUE OF CAT THE LOCATION (X,Y) FORSOME LOC SIGIN "LOC SIG BAG"; (B) INTERPOLATE/EXTRAPOLATE A VALUE FOR THE C-COORDINATE OF "EST LOC SIG" AT THE LOCATION, "LOC FORESTIMATION"

ASSIGNA DEFAULT VALUE TO ANY UNDEFINED LOCSIG FIELDS OF "EST LOC SIG"

RETURN FIG. 21 "EST"LOC SIG" U.S. Patent Sep. 15, 2015 Sheet 38 of 62 US 9,134,398 B2

LOC AREA TYPE-- GET THE AREA TYPE(S) FOR "LOC"

SEARCH AREA- GET A DEFAULT MAXIMUM SEARCH AREA HAVING "LOC"

SAVED SEARCH AREA-SEARCH AREA SEARCH AREA TYPES GET THE (FUZZY LOGIC) AREA TYPE(S) FOR "SEARCH AREA"

MIN ACCEPTABLE NBR LOC SIGS--0

AREA TYPE-- GET FIRST (NEXT) AREA TYPE IN "SEARCH AREA TYPES" DOES "AREA TYPE" REFERENCE yes (O’soA NEW AREA TYPE

TOTAL NBR LOC SIGS--THE NUMBER OF VERIFIED LOC SIGSIN THE LOCATION SIGNATURE DATA BASE 1320 HAVING ALOCATION (THE "MS LOC" ATTRIBUTE) IN "SEARCH AREA" IS"MIN ACCEPTABLE NBR LOC SIGS" > "TOTAL NBR LOC SIGS"? YES C NO

RETURN "SAVED SEARCHED AREA" FIG. 22A U.S. Patent Sep. 15, 2015 Sheet 39 of 62 US 9,134,398 B2

SAVED SEARCH AREA- SEARCH AREA

SEARCH AREA – GET A SMALLER AREA FOR "SEARCH AREA", WHEREN THIS SMALLER AREA STILL CONTAINS "LOC".

AREA PERCENT-PERCENTAGE OF AREA FOR "SEARCH AREA" THAT IS OF THE TYPE "AREA TYPE", OR, USING FUZZY LOGIC, HAVING A FUZZYVALUE ABOVE A PREDETERMINED THRESHOLD.

MIN ACCEPTABLE NBR LOC SIGS -- MIN ACCEPTABLE NBR LOC SIGS + (MINIMUMACCEPTABLE VERIFIED LOCSIG DENSITY FOR "AREA TYPE") * (SIZEOF(SEARCH AREA) * (AREA PERCENT / 100)

FIG. 22B

U.S. Patent Sep. 15, 2015 Sheet 43 of 62 US 9,134,398 B2

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U.S. Patent Sep. 15, 2015 Sheet 45 of 62 US 9,134,398 B2

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U.S. Patent Sep. 15, 2015 Sheet 46 of 62 US 9,134,398 B2

FIG. 26A 204CA LOC HYP LIST-CREATE AN EMPTY NEW y LOCATION HYPOTHESIS LIST AND PUT "LOC HYP ON THIS LIST. 208CA MESH-- GET A MESH OF AREA CELLS RELATED TO THE FIRST ORDERMODEL THAT GENERATED "LOC HYP". 212CA PT MIN AREA-GET A "SMALL" AREA ABOUT AN TESTIMATED TARGET MS POINT LOCATION PROVIDED BY "LOC HYP", WHEREIN THIS AREA INCLUDES ONE OR MOREMESH CELLSSURROUNDING THE TARGET MS PONT LOCATION. 216CA INITIALIZE A VARIABLE, "AREA", WITH "PT MN AREA". 220CA PT MAX AREA-GET A MAXIMUM AREA ABOUT THE ESTIMATED TARGET MS POINT LOCATION PROVIDED BY "LOC HYP".

MIN CLUSTERS- GET THE MINIMUM NUMBER OF PREVIOUS MS 140 LOCATION ESTIMATES, L, THAT ARE DESIRED IN THE AREA, "AREA", FOR SUBSTANTIALLY RELYING ON HISTORICALMS LOCATION DATA IN THE LOCATION SIGNATURE DATA BASE 1320 FOR ADJUSTING THE CONFIDENCE AND/OR THE TARGET MS ESTIMATED LOCATION, WHEREEN EACH SUCH MS ESTIMATE WAS GENERATED BY THE SAME FIRST ORDER MODEL THAT GENERATED "LOC HYP".

220CA PT EST BAG--GET THE MS POINT LOCATION ESTIMATES FOREACH PREVIOUS MS LOCATION ESTIMATE, L, 224CA COUNTED IN THE PREVIOUS STEP. U.S. Patent Sep. 15, 2015 Sheet 47 of 62 US 9,134,398 B2

WIILE THE NUMBER OF POINT LOCATION ESTIMATES IN "PT EST BAG" IS LESS THAN "MIN CLUSTERS" AND "AREA" REPRESENTS AN AREA LESS THAN OR EQUAL TO "PT MAX AREA": (A) REPEATEDLY INCREASE "AREA"; (B) RECALCULATE "MIN CLUSTERS" FOR "AREA" ACCORDING TO STEP 224CA, (C) RECALCULATE "PT TEST BAG" FOR "AREA" ACCORDING TO STEP 228CA. 232CA ASSIGN THE RESULTING VALUE FOR "AREA" AS THE VALUE FOR THE "PT COVERING" ATTRIBUTE OF "LOC HYP". IS "PT EST BAG" 236CA 240CA EMPTY)- -

NO YES (SO CANNOT ADJUST 244CA "LOC HYP") 252CA

DETERMINE THE VALUE, MIN{(SIZE OF SET THE (PT EST BAG)/MIN CLUSTERS), 1.0 AS "IMAGE AREA" A CONFIDENCE ADJUSTMENT ATTRIBUTE OF COEFFICIENT; ASSIGN THIS VALUE TO "LOC HYP" TONULL. THE PARAMETER, "CLUSTER RATIO FACTOR". RETURN WITH "LOC HYP LIST" DOES "AREA" REPRESENT AN AREA LARGER 256CA THAN THE AREA FOR "PT MAX AREA"? 248CA NO C YES (SO"AREA" IS TOO BIG TO ENTIRELY IGNORE INITIAL MS LOCATION ESTIMATE AND CONFIDENCE). FIG. 26B NEW LOC HYP - CREATE A DUPLICATE OF "LOC HYP" WITH THE "IMAGE AREA"ATTRIBUTE SET TONULL, AND WITH THE CONFIDENCE VALUE LOWERED BY THE COEFFICIENT. 260CA (1.0 - CLUSTERRATIO FACTOR). U.S. Patent Sep. 15, 2015 Sheet 48 of 62 US 9,134,398 B2

ADD NEw LOC HYP" TO "LOC HYP LIST".

IMAGE CLUSTER SET-- GET THE VERIFIED LOCATION SIGNATURE CLUSTERS IN THE LOCATION SIGNATURE DATA BASE FOR WHICH THERE ARE MS POINT LOCATION ESTIMATES IN "PT EST BAG". 268CA

IMAGE AREA-GET A "SMALL" AREA CONTAINING THE VERIFED LOCATION SIGNATURES IN "IMAGE CLUSTER SET".

272CA 276CA ASSIGN THE VALUE OF "IMAGE AREA" TO THE "IMAGE AREA"ATTRIBUTE FIELD OF "LOC HYP".

280CA CONFIDENCE--INVOKE THE FUNCTION, "CONFIDENCE ADJUSTER", FOR DETERMINING A CONFIDENCE VALUE FOR THE TARGET MS BEING IN THE AREA FOR "IMAGE AREA". THE INVOCATION INPUT VALUES ARE: "LOC HYPFOM ID", "IMAGE AREA", "IMAGE CLUSTER SET".

ASSIGN THE VALUE OF: "CONFIDENCE * 284CA CLUSTER RATIO FACTOR" TO THE "CONFIDENCE" ATTRIBUTE OF "LOC HYP".

RETURN WITH "LOC HYP LIST" 288CA FIG. 26C

U.S. Patent Sep. 15, 2015 Sheet 58 of 62 US 9,134,398 B2

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U.S. Patent US 9,134,398 B2

U.S. Patent Sep. 15, 2015 Sheet 62 of 62 US 9,134,398 B2

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US 9,134,398 B2 1. 2 WRELESS LOCATION USING NETWORK the commercial version of GPS) from a time-based signal CENTRC LOCATION ESTMATORS received simultaneously from at least three satellites. A ground-based GPS receiver at or near the object to be located RELATED APPLICATIONS determines the difference between the time at which each satellite transmits a time signal and the time at which the The present application is a continuation-in-part of U.S. signal is received and, based on the time differentials, deter application Ser. No. 1 1/739,097 filed Apr. 24, 2007, which is mines the object's location. However, the GPS is impractical a continuation of U.S. application Ser. No. 09/194,367 filed in many applications. The signal power levels from the satel Nov. 24, 1998, now U.S. Pat. No. 7,764,231, which is the lites are low and the GPS receiver requires a clear, line-of National Stage of International Application No. PCT/US97/ 10 sight path to at least three satellites above a horizon of about 15892, filed Sep. 8, 1997, which claims the benefit of the 60 degrees for effective operation. Accordingly, inclement following three provisionals: U.S. Provisional Application weather conditions, such as clouds, terrain features, such as No. 60/056,590 filed Aug. 20, 1997: U.S. Provisional Appli hills and trees, and buildings restrict the ability of the GPS cation No. 60/044,821 filed Apr. 25, 1997; and U.S. Provi 15 receiver to determine its position. Furthermore, the initial sional Application No. 60/025,855 filed Sep. 9, 1996; each of GPS signal detection process for a GPS receiver is relatively the above identified applications are incorporated hereinfully long (i.e., several minutes) for determining the receiver's by reference. position. Such delays are unacceptable in many applications FIELD OF THE INVENTION Such as, for example, emergency response and vehicle track ing. The present invention is directed generally to a system and Differential GPS, or DGPS systems offer correction method for locating people or objects, and in particular, to a schemes to account for time synchronization drift. Such cor system and method for locating a wireless mobile station rection schemes include the transmission of correction sig using a plurality of simultaneously activated mobile station nals over a two-way radio link or broadcast via FM radio location estimators. 25 station subcarriers. These systems have been found to be awkward and have met with limited Success. BACKGROUND Additionally, GPS-based location systems have been attempted in which the received GPS signals are transmitted Introduction to a central data center for performing location calculations. 30 Such systems have also met with limited success. In brief, Wireless communications systems are becoming increas each of the various GPS embodiments have the same funda ingly important worldwide. Wireless cellular telecommuni mental problems of limited reception of the satellite signals cations systems are rapidly replacing conventional wire and added expense and complexity of the electronics required based telecommunications systems in many applications. for an inexpensive location mobile station or handset for Cellular radio telephone networks (“CRT), and specialized 35 detecting and receiving the GPS signals from the satellites. mobile radio and mobile data radio networks are examples. Radio Propagation Background The general principles of wireless cellular telephony have The behavior of a mobile radio signal in the general envi been described variously, for example in U.S. Pat. No. 5.295, ronment is unique and complicated. Efforts to perform cor 180 to Vendetti, et al., which is incorporated herein by refer relations between radio signals and distance between a base CCC. 40 station and a mobile station are similarly complex. Repeated There is great interest in using existing infrastructures for attempts to solve this problem in the past have been met with wireless communication systems for locating people and/or only marginal Success. Factors include terrain undulations, objects in a cost effective manner. Such a capability would be fixed and variable clutter, atmospheric conditions, internal invaluable in a variety of situations, especially in emergency radio characteristics of cellular and PCS systems, such as or crime situations. Due to the substantial benefits of such a 45 frequencies, antenna configurations, modulation schemes, location system, several attempts have been made to design diversity methods, and the physical geometries of direct, and implement Such a system. refracted and reflected waves between the base stations and Systems have been proposed that rely upon signal strength the mobile. Noise. Such as man-made externally sources (e.g., and trilateralization techniques to permit location include auto ignitions) and radio system co-channel and adjacent those disclosed in U.S. Pat. Nos. 4,818,998 and 4,908,629 to 50 channel interference also affect radio reception and related Apsell et al. (“the Apsell patents”) and 4,891,650 to Sheffer performance measurements, such as the analog carrier-to (“the Sheffer patent). However, these systems have draw interference ratio (C/I), or digital energy-per-bit/Noise den backs that include high expense in that special purpose elec sity ratio (Ex) and are particular to various points in time tronics are required. Furthermore, the systems are generally and space domains. only effective in line-of-sight conditions, such as rural set 55 RF Propagation in Free Space tings. Radio wave surface reflections, refractions and ground Before discussing real world correlations between signals clutter cause significant distortion, in determining the loca and distance, it is useful to review the theoretical premise, that tion of a signal source in most geographical areas that are of radio energy path loss across a pure isotropic Vacuum more than sparsely populated. Moreover, these drawbacks are propagation channel, and its dependencies within and among particularly exacerbated in dense urban canyon (city) areas, 60 various communications channel types. FIG. 1 illustrates a where errors and/or conflicts in location measurements can definition of channel types arising in communications: result in Substantial inaccuracies. Over the last forty years various mathematical expressions Another example of a location system using time of arrival have been developed to assist the radio mobile cell designer in and triangulation for location are satellite-based systems, establishing the proper balance between base station capital such as the military and commercial versions of the Global 65 investment and the quality of the radio link, typically using Positioning Satellite system (“GPS). GPS can provide accu radio energy field-strength, usually measured in microvolts/ rate position determination (i.e., about 100 meters error for meter, or decibels. US 9,134,398 B2 3 4 First consider Hata's single ray model. A simplified radio mura, et al, Review of the Electrical Communications labo channel can be described as: ratory, Vol 16, pp 825-873, September-October 1968. G. --L--F+L+L+L-G+G. (Equation 1) The typical urban Hata model for L, was defined as L. L. where L-69.55+26.16 log(f)-13.82 log(h)-a(his)+ G, System gain in decibels ((44.9-6.55 log(His)log(a)dB) (Equation 4) L free space path loss in dB, where F=fade margin in dB, L. path loss, Hata urban L-transmission line loss from coaxials used to connect his base station antenna height radio to antenna, in dB, 10 his mobile station antenna height L. miscellaneous losses such as minor antenna misalign d=distance BS-MS in km ment, coaxial corrosion, increase in the receiver noise a(his) is a correction factor for Small and medium sized figure due to aging, in dB, cities, found to be: L. branching loss due to filter and circulator used to com 1 log(f-0.7)h-1.56 log(f-0.8) a (has) (Equation 5) bine or split transmitter and receiver signals in a single 15 antenna For large cities the correction factor was found to be: G, gain of transmitting antenna a(his)=3.2(log 11.75hs-4.97 (Equation 6) G, gain of receiving antenna Free space path loss' L., as discussed in Mobile Communica assuming fis equal to or greater than 400 mHz. tions Design Fundamentals, William C.Y. Lee, 2nd, Ed across The typical suburban model correction was found to be: the propagation channel is a function of distanced, frequency f (for f values.<1 GHz, such as the 890-950 mHz cellular 2 (Equation 7) band): LH, but LHu 2 of - 5.4 dB C

25 P 1 (equation 2) The typical rural model modified the urban formula differ P, (4 die? ently, as seen below: Litt-L-4.78(log f’--18.33 log.f 40.94 (dB) (Equation 8) where Preceived power in free space 30 Although the Hata model was found to be useful for gen P. transmitting power eralized RF wave prediction in frequencies under 1 GHz in c-speed of light, certain suburban and rural settings, as either the frequency The difference between two received signal powers in free and/or clutter increased, predictability decreased. In current Space, practice, however, field technicians often have to make a 35 guess for dense urban an Suburban areas (applying whatever model seems best), then installing a base stations and begin taking manual measurements. Coverage problems can take Por-2 d (equation 3) up to a year to resolve. arl ) (20)logy (dB) Relating Received Signal Strength to Location 40 Having previously established a relationship between d indicates that the free propagation path loss is 20 dB per and P, reference equation 2 above: d represents the distance decade. Frequencies between 1 GHz and 2 GHz experience between the mobile station (MS) and the base station (BS); increased values in the exponent, ranging from 2 to 4, or 20 to Prepresents the received power in free space) for a given set 40 dB/decade, which would be predicted for the new PCS of unchanging environmental conditions, it may be possible 1.8-1.9 GHz band. 45 to dynamically measure P and then determine d. This suggests that the free propagation path loss is 20 dB In 1991, U.S. Pat. No. 5,055,851 to Sheffer taught that if per decade. However, frequencies between 1 GHz, and 2 GHz three or more relationships have been established in a trian experience increased values in the exponent, ranging from 2 gular space of three or more base stations (BSS) with a loca to 4, or 20 to 40 dB/decade, which would be predicted for the tion database constructed having data related to possible new PCS 1.8-1.9 GHz band. One consequence from a loca 50 mobile station (MS) locations, then arculation calculations tion perspective is that the effective range of values for higher may be performed, which use three distinct P. measurements exponents is an increased at higher frequencies, thus provid to determine an X,Y, two dimensional location, which can ing improved granularity of ranging correlation. then be projected onto an area map. The triangulation calcu Environmental Clutter and RF Propagation Effects lation is based on the fact that the approximate distance of the Actual data collected in real-world environments uncov 55 mobile station (MS) from any base station (BS) cell can be ered huge variations with respect to the free space path loss calculated based on the received signal strength. Sheffer equation, giving rise to the creation of many empirical for acknowledges that terrain variations affect accuracy, mulas for radio signal coverage prediction. Clutter, either although as noted above. Sheffers disclosure does not fixed or stationary in geometric relation to the propagation of account for a sufficient number of variables, such as fixed and the radio signals, causes a shadow effect of blocking that 60 variable location shadow fading, which are typical in dense perturbs the free space loss effect. Perhaps the best known urban areas with moving traffic. model set that characterizes the average path loss is Hatas, Most field research before about 1988 has focused on char “Empirical Formula for Propagation Loss in Land Mobile acterizing (with the objective of RF coverage prediction) the Radio', M. Hata, IEEE Transactions VT-29, pp. 317-325, RF propagation channel (i.e., electromagnetic radio waves) August 1980, three pathloss models, based on Okumura's 65 using a single-ray model, although standard fit errors in measurements in and around Tokyo, “Field Strength and its regressions proved dismal (e.g., 40-80 dB). Later, multi-ray Variability in VHF and UHF Land Mobile Service', Y. Oku models were proposed, and much later, certain behaviors US 9,134,398 B2 5 6 were studied with radio and digital channels. In 1981, Vogler measurements to the RF propagation channel signal strength proposed that radio waves at higher frequencies could be alone. However, Greenstein based his finding on two Suspi modeled using optics principles. In 1988 Walfisch and Ber cious assumptions: 1) he assumed that distance correlation toni applied optical methods to develop a two-ray model, estimates were identical for uplink and downlink transmis which when compared to certain highly specific, controlled sion paths; and 2) modulation techniques would be transpar field data, provided extremely good regression fit standard ent in terms of improved distance correlation conclusions. errors of within 1.2 dB. Although some data held very correlations, other data and In the Bertoni two ray model it was assumed that most environments produced poor results. Accordingly, his results cities would consist of a core of high-rise buildings Sur appear unreliable for use in general location context. rounded by a much larger area having buildings of uniform 10 In 1993 Greenstein, etal, authored “A Measurement-Based height spread over regions comprising many square blocks, Model for Predicting Coverage Areas of Urban Microcells'. with Street grids organizing buildings into rows that are nearly in the IEEE Journal On Selected Areas in Communications, parallel. Rays penetrating buildings then emanating outside a Vol. 11, No. 7, 9/93. Greenstein reported a generic measure building were neglected. FIG. 2 provides a basis for the vari ment-based model of RF attenuation in terms of constant ables. 15 value contours Surrounding a given low-power, low antenna After a lengthy analysis it was concluded that path loss was microcell environment in a dense, rectilinear neighborhood, a function of three factors: (1) the path loss between antennas such as New York City. However, these contours were for the in free space; (2) the reduction of rooftop wave fields due to cellular frequency band. In this case, LOS and non-LOS clutter were considered for a given microcell site. A result of settling; and (3) the effect of diffraction of the rooftop fields this analysis was that RF propagation losses (or attenuations), down to ground level. The last two factors were summarily when cell antenna heights were relatively low, provided termed L, given by: attenuation contours resembling a spline plane curve depicted as anasteroid, aligned with major Street grid patterns. Further, Let = (Equation 9) Greenstein found that convex diamond-shaped RF propaga 25 tion loss contours were a common occurrence in field mea 2 Surements in a rectilinear urban area. The special plane curve 57.1 + A + log(f) + R-(18 log(H)) - 18 logi 17 n asteroid is represented by the formula x+y=r'. How ever, these results alone have not been sufficiently robust and The influence of building geometry is contained in A: general to accurately locate an MS, due to the variable nature 30 of urban clutter spatial arrangements. At Telesis Technology in 1994 Howard Xia, etal, authored d Y2 (Equation 10) “Microcellular Propagation Characteristics for Personal A = slog() –9logd +20log {tan2(h - Hits)} Communications in Urban and Suburban Environments', in IEEE Transactions of Vehicular Technology, Vol.43, No. 3, 35 8/94, which performed measurements specifically in the PCS However, a substantial difficulty with the two-ray model in 1.8 to 1.9 GHz frequency band. Xia found corresponding but practice is that it requires a Substantial amount of data regard more variable outcome results in San Francisco, Oakland ing building dimensions, geometries, street widths, antenna (urban) and the Sunset and Mission Districts (suburban). gain characteristics for every possible ray path, etc. Addition Summary of Factors Affecting RF Propagation ally, it requires an inordinate amount of computational 40 The physical radio propagation channel perturbs signal resources and Such a model is not easily updated or main strength, frequency (causing rate changes, phase delay, signal tained. to noise ratios (e.g., C/I for the analog case, or E, RF Unfortunately, in practice clutter geometries and building energy per bit, over average noise density ratio for the digital heights are random. Moreover, data of sufficient detail has case) and Doppler-shift. Signal strength is usually character been extremely difficult to acquire, and regression standard fit 45 ized by: errors are poor; i.e., in the general case, these errors were Free Space Path Loss (L) found to be 40-60 dB. Thus the two-ray model approach, Slow fading loss or margin (L) although sometimes providing an improvement over single Fast fading loss or margin (L) ray techniques, still did not predict RF signal characteristics Loss due to slow fading includes shadowing due to clutter in the general case to level of accuracy desired (<10 dB). 50 blockage (sometimes included in Lp). Fast fading is com Work by Greenstein has since developed from the perspec posed of multipath reflections which cause: 1) delay spread; tive of measurement-based regression models, as opposed to 2) random phase shift or Rayleigh fading; and 3) random the previous approach of predicting-first, then performing frequency modulation due to different Doppler shifts on dif measurement comparisons. Apparently yielding to the fact ferent paths. that low-power, low antenna (e.g., 12-25 feet above ground) 55 Summing the path loss and the two fading margin loss height PCS microcell coverage was insufficient in urban components from the above yields a total path loss of: buildings, Greenstein, et al., authored “Performance Evalua tions for Urban Line-of-sight Microcells Using a Multi-ray LtotalLotLslot fast Propagation Model, in IEEE Globecom Proceedings, Referring to FIG.3, the figure illustrates key components of a December 1991. This paper proposed the idea of formulating 60 typical cellular and PCS power budget design process. The regressions based on field measurements using Small PCS cell designer increases the transmitted power P by the microcells in a lineal microcell geometry (i.e., geometries in shadow fading margin L, which is usually chosen to be which there is always a line-of-sight (LOS) path between a within the 1-2 percentile of the slow fading probability den subscriber's mobile and its current microsite). sity function (PDF) to minimize the probability of unsatisfac Additionally, Greenstein studied the communication chan 65 torily low received power level P. at the receiver. The P. nels variable Bit-Error-Rate (BER) in a spatial domain, which level must have enough signal to noise energy level (e.g., 10 was a departure from previous research that limited field dB) to overcome the receiver's internal noise level (e.g., -118 US 9,134,398 B2 7 8 dBm in the case of cellular 0.9 GHz), for a minimum voice wireless communications with mobile stations for other pur quality standard. Thus in the example P. must never be poses such as Voice communication and/or visual communi below -108 dBm, in order to maintain the quality standard. cation (Such as text paging, graphical or video communica Additionally the short term fast signal fading due to mul tions). Related objectives for the present disclosure include tipath propagation is taken into account by deploying fast providing a system and method that: fading margin L, which is typically also chosen to be a few (1.1) can be readily incorporated into existing commercial percentiles of the fast fading distribution. The 1 to 2 percen wireless telephony systems with few, if any, modifications of tiles compliment other network blockage guidelines. For a typical telephony wireless infrastructure; example the cell base station traffic loading capacity and (1.2) can use the native electronics of typical commercially network transport facilities are usually designed for a 1-2 10 percentile blockage factor as well. However, in the worst-case available, or likely to be available, telephony wireless mobile scenario both fading margins are simultaneously exceeded, stations (e.g., handsets) as location devices; thus causing a fading margin overload. (1.3) can be used for effectively locating people and/or In Roy, Steele's, text, Mobile Radio Communications, objects wherein there are few (if any) line-of-sight wireless IEEE Press, 1992, estimates for a GSM system operating in 15 receivers for receiving location signals from a mobile station the 1.8 GHz band with a transmitter antenna height of 6.4 m (herein also denoted MS); and an MS receiver antenna height of 2 m, and assumptions (1.4) can be used not only for decreasing location determining regarding total path loss, transmitter power would be calcu difficulties due to multipath phenomena but in fact uses such lated as follows: multipath for providing more accurate location estimates; (1.5) can be used for integrating a wide variety of location TABLE 1. techniques in a straight-forward manner, and (1.6) can Substantially automatically adapt and/or (re)train GSM Power Budget Example and/or (re)calibrate itself according to changes in the envi Parameter dBm value Will require ronment and/or terrain of a geographical area where the 25 present disclosure is utilized; and slow 14 (1.7) can utilize a plurality of wireless location estimators fast 7 Llpath 110 based on different wireless location technologies (e.g., GPS Min. RXpwr required -104 location techniques, terrestrial base station signal timing TXpwr = 27 dBm techniques for triangulation and/or trilateration, wireless sig 30 nal angle of arrival location techniques, techniques for deter mining a wireless location within a building, techniques for Steele's sample size in a specific urban London area of 80,000 determining a mobile station location using wireless location LOS measurements and data reduction found a slow fading data collected from the wireless coverage area for, e.g., loca variance of tion techniques using base station signal coverage areas, Sig 35 nal pattern matching location techniques and/or stochastic assuming log normal slow fading PDF and allowing for a techniques), wherein each Such estimator may be activated 1.4% slow fading margin overload, thus independently of one another, whenever Suitable data is pro vided thereto and/or certain conditions, e.g., specific to the slow estimator are met; The fast fading margin was determined to be: 40 (1.8) can provide a common interface module from which a plurality of the location estimators can be activated and/or L–7 dB provided with input; In contrast, Xia's measurements in urban and Suburban (1.9) provides resulting mobile station location estimates to California at 1.8 GHz uncovered flat-land shadow fades on location requesting applications (e.g., for 911 emergency, the the order of 25-30 dB when the mobile station (MS) receiver 45 fire or police departments, taxi services, vehicle location, was traveling from LOS to non-LOS geometries. In hilly etc.) via an output gateway, wherein this gateway: terrain fades of +5 to -50 dB were experienced. Thus it is (a) routes the mobile station location estimates to the evident that attempts to correlate signal strength with MS appropriate location application(s) via a communica ranging distance Suggest that error ranges could not be tions network Such as a wireless network, a public expected to improve below 14 dB, with a high side of 25 to 50 50 Switched telephone network, a short messaging service dB. Based on 20 to 40 dB per decade, Corresponding error (SMS), and the Internet, ranges for the distance variable would then be on the order of (b) determines the location granularity and representation 900 feet to several thousand feet, depending upon the particu desired by each location application requesting a loca lar environmental topology and the transmitter and receiver tion of a mobile station, and/or geometries. 55 (c) enhances the received location estimates by, e.g., per forming additional processing Such as 'snap to Street' SUMMARY functions for mobile stations known to reside in a vehicle. It is an objective of the present disclosure to provide a Yet another objective is to provide a low cost location system and method for to wireless telecommunication sys 60 system and method, adaptable to wireless telephony systems, tems for accurately locating people and/or objects in a cost for using simultaneously a plurality of location techniques for effective manner. Additionally, it is an objective of the present synergistically increasing MS location accuracy and consis disclosure to provide Such location capabilities using the tency. measurements from wireless signals communicated between It is yet another objective of the present disclosure that at mobile stations and a network of base stations, wherein the 65 least some of the following MS location techniques can be same communication standard or protocol is utilized for loca utilized by various embodiments of the present disclosure: tion as is used by the network of base stations for providing (2.1) time-of-arrival wireless signal processing techniques; US 9,134,398 B2 10 (2.2) time-difference-of-arrival wireless signal processing (MSC). Such a component provides communications and techniques; control connectivity among base stations and the public tele (2.3) adaptive wireless signal processing techniques having, phone network 124 (FIG. 4). for example, learning capabilities and including, for instance, (3.4) The phrase, "composite wireless signal characteristic artificial neural net and genetic algorithm processing: values' denotes the result of aggregating and filtering a col (2.4) signal processing techniques for matching MS location lection of measurements of wireless signal samples, wherein signals with wireless signal characteristics of known areas; these samples are obtained from the wireless communication (2.5) conflict resolution techniques for resolving conflicts in between an MS to be located and the base station infrastruc hypotheses for MS location estimates; ture (e.g., a plurality of networked base stations). However, (2.6) enhancement of MS location estimates through the use 10 other phrases are also used herein to denote this collection of derived characteristic values depending on the context and the of both heuristics and historical data associating MS wireless likely orientation of the reader. For example, when viewing signal characteristics with known locations and/or environ these values from a wireless signal processing perspective of mental conditions. radio engineering, as in the descriptions of the Subsequent Yet another objective is to provide location estimates in 15 Detailed Description sections concerned with the aspects for terms of time vectors, which can be used to establish motion, receiving MS signal measurements from the base station speed, and an extrapolated next location in cases where the infrastructure, the phrase typically used is: “RF signal mea MS signal Subsequently becomes unavailable. Surements'. Alternatively, from a data processing perspec tive, the phrases: “location signature cluster and “location DEFINITIONS signal data” are used to describe signal characteristic values between the MS and the plurality of infrastructure base sta The following definitions are provided for convenience. In tions Substantially simultaneously detecting MS transmis general, the definitions here are also provided elsewhere in sions. Moreover, since the location communications between this document as well. an MS and the base station infrastructure typically include (3.1) The term “wireless' herein is, in general, an abbrevia 25 simultaneous communications with more than one base sta tion for “digital wireless', and in particular, “wireless' refers tion, a related useful notion is that of a "location signature' to digital radio signaling using one of standard the wireless which is the composite wireless signal characteristic values protocols such as CDMA, NAMPS, AMPS, TDMA, GSM, for signal samples between an MS to be located and a single GPRS, Bluetooth, and/or WIFI as one skilled in the art will base station. Also, in some contexts, the phrases: "signal understand. 30 characteristic values' or 'signal characteristic data” are used (3.2) As used herein, the term “mobile station' (equivalently, when either or both a location signature(s) and/or a location MS) refers to a wireless device that is at least a transmitting signature cluster(s) are intended. device, and in most cases is also a wireless receiving device, SUMMARY Such as a portable radio telephony handset a radio identifica 35 tion tag (e.g., for a person or equipment), and a computer The present disclosure relates to a wireless mobile station having the capability for wireless access to the Internet. Note location system and method for performing wireless location that in some contexts herein instead of, or in addition to, the of mobile stations. In particular, the present disclosure is terms “mobile station” or “MS, the following terms may be directed to hybriding, combining or otherwise using wireless synonymously also used: “personal station’ (PS), and “loca 40 location determining techniques that estimate a geographical tion unit (LU). location(s) of each of one or more mobile stations using, for (3.3) The term, “infrastructure', denotes a communications each Such mobile station, wireless signal characteristics from network having a wireless communication capability, e.g., one or more of: (i) a signal strength, a time of arrival, or time telephony wireless communication/Internet services, and difference of arrival of wireless signals communicated more particularly, that portion of such a network that receives 45 between the mobile station, and terrestrial base stations, and/ and processes wireless communications with wireless mobile or (ii) wireless signal direction information of wireless sig stations. In particular, this infrastructure includes wireless nals communicated between the mobile station, and terres base stations (BS) such as those for radio mobile communi trial base stations. In particular, depending on the wireless cation systems based on CDMA, AMPS, NAMPS, TDMA, signals obtained for determining a geolocation of a mobile GSM, GPRS, and WIFI wherein the base stations provide: (i) 50 station, wireless signal characteristics: from (i) only above a network of cooperative communication channels for wire may be used, or from (ii) only above may be used, or from lessly communicating with MSs, and (ii) in at least in some both (i) and (ii) above may used. embodiments, a conventional telecommunications interface In one embodiment, the present disclosure is directed to with a Mobile Switch Center (MSC). Note that the term “base what is known as “network centric' wireless location tech station' is also referred to in the art, in various embodiments, 55 niques between one of the mobile stations and a network of as an “access point, particularly when the infrastructure is terrestrial (Earth supported) base stations. local (and possibly proprietary or private) to a single entity Regarding a wireless location gateway, this term refers to a Such as a hospital, university, governmental facility and the communications network node whereat a plurality of location like. Typically a base station provides two-way wireless com requests are received for locating various mobile stations munication with one or more mobile stations in a wireless 60 from various sources (e.g., for E911 requests, for stolen coverage area (volume) for the base station. Moreover, a MS vehicle location, for tracking of vehicles traveling cross coun user within an area wirelessly serviced by a network of base try, etc.), and for each Such request and the corresponding stations may be provided with wireless communication mobile station to be located, this node: (a) activates one or throughout the area by user transparent communication trans more wireless location estimators for locating the mobile fers (i.e., “handoffs') between the user's MS and these base 65 station, (b) receives one or more location estimates of the stations in order to maintain effective wireless communica mobile station from the location estimators, and (c) transmits tion service. If such a network includes a mobile switch center a resulting location estimate(s) to, e.g., an application which US 9,134,398 B2 11 12 made the request. Moreover, Such a gateway typically will lized for determining the mobile station's location (e.g., likely activate location estimators according to the particulars intersecting Such coverage areas for determining a loca of each individual wireless location request, e.g., the avail tion); ability of input data needed by particular location estimators. (f) Location techniques that use communications from low Additionally, Such a gateway will typically have sufficiently power, low functionality base stations (denoted “loca well defined uniform interfaces so that such location estima tion base stations'); and tors can be added and/or deleted to, e.g., provide different (g) Any other location techniques that may be deemed location estimators for performing wireless location different worthwhile to incorporate into an embodiment of the coverage areas. present disclosure. The present disclosure encompasses such wireless location 10 Accordingly, Some embodiments of the present disclosure gateways. Thus, for locating an identified mobile station, the may be viewed as platforms for integrating wireless location location gateway embodiments of the present disclosure may techniques in that wireless location computational models activate one or more of a plurality of location estimators (denoted “first order models” or “FOMs' hereinbelow) may depending on, e.g., (a) the availability of particular types of 15 be added and/or deleted from such embodiments of the inven wireless location data for locating the mobile station, and (b) tion without changing the interface to further downstream the location estimators accessible by the location gateway. processes. That is, one aspect of the invention is the specifi Moreover, a plurality of location estimators may be activated cation of a common data interface between Such computa for locating the mobile station in a single location, or different tional models and Subsequent location processing such as ones of Such location estimators may be activated to locate the processes for combining of location estimates, tracking mobile station at different locations. Moreover, the location mobile stations, and/or outputting location estimates to loca gateway of the present disclosure may have incorporated tion requesting applications. therein one or more of the location estimators, and/or may Moreover, it should be noted that the present disclosure access geographically distributed location estimators via also encompasses various hybrid approaches to wireless loca requests through a communications network Such as the Inter 25 tion, wherein various combinations of two or more of the net. location techniques (a) through (g) immediately above may In particular, the location gateway of the present disclosure be used in locating a mobile station at Substantially a single may access, in various instances of locating mobile stations, location. Thus, location information may be obtained from a various location estimators that utilize one or more of the plurality of the above location techniques for locating a following wireless location techniques: 30 mobile station, and the output from Such techniques can be synergistically used for deriving therefrom an enhanced loca (a) A GPS location technique such as, e.g., one of the GPS tion estimate of the mobile station. location techniques as described in the Background sec It is a further aspect of the present disclosure that it may be tion hereinabove; used to wirelessly locate a mobile station: (a) from which a (b) A technique for computing a mobile station location 35 911 emergency call is performed, (b) for tracking a mobile that is dependent upon geographical offsets of the station (e.g., a truck traveling across country), (c) for routing mobile station from one or more terrestrial transceivers a mobile station, and (d) locating people and/or animals, (e.g., base stations of a commercial radio service pro including applications for confinement to (and/or exclusion vider). Such offsets may be determined from signal time from) certain areas. delays between Such transceivers and the mobile station, 40 It is a further aspect of the present disclosure that it such a such as by time of arrival (TOA) and/or time difference wireless mobile station location system may be decomposed of arrival (TDOA) techniques as is discussed further into: (i) a first low level wireless signal processing Subsystem hereinbelow. Moreover, such offsets may be determined for receiving, organizing and conditioning low level wireless using both the forward and reverse wireless signal tim signal measurements from a network of base stations coop ing measurements of transmissions between the mobile 45 eratively linked for providing wireless communications with station and Such terrestrial transceivers. Additionally, mobile stations (MSS); and (ii) a second high level signal such offsets may be directional offsets, wherein a direc processing Subsystem for performing high level data process tion is determined from such a transceiver to the mobile ing for providing most likelihood location estimates for station; mobile stations. (c) Various wireless signal pattern matching, associative, 50 Thus, the present disclosure may be considered as a novel and/or stochastic techniques for performing compari signal processor that includes at least the functionality for the Sons and/or using a learned association between: high level signal processing Subsystem mentioned herein (i) characteristics of wireless signals communicated above. Accordingly, assuming an appropriate ensemble of between a mobile station to be located and a network wireless signal measurements characterizing the wireless sig of wireless transceivers (e.g., base stations), and 55 nal communications between a particular MS and a net (ii) previously obtained sets of characteristics of wire worked wireless base station infrastructure have been less signals (from each of a plurality of locations), received and appropriately filtered of noise and transitory wherein each set was communicated, e.g., between a values (such as by an embodiment of the low level signal network of transceivers (e.g., the fixed location base processing Subsystem disclosed in a copending PCT patent stations of a commercial radio service provider), and, 60 application PCT/US97/15933 titled, “Wireless Location some one of the mobile stations available for commu Using A Plurality of Commercial Network Infrastructures.” nicating with the network; by F. W. LeBlanc et al., filed Sep. 8, 1997 from which U.S. (d) Indoor location techniques using a distributed antenna Pat. No. 6,236,365, filed Jul. 8, 1999 is the U.S. national system; counterpart, these two references being herein fully incorpo (e) Techniques for locating a mobile station, wherein, e.g., 65 rated by reference), the present disclosure uses the output wireless coverage areas of individual fixed location from Such a low level signal processing system for determin transceivers (e.g., fixed location base stations) are uti ing a most likely location estimate of an MS. US 9,134,398 B2 13 14 That is, once the following steps are appropriately per corresponding MS estimated area, wherein (as described formed (e.g., by the LeBlanc U.S. Pat. No. 6,236.365): hereinbelow) -1 indicates that the target MS is absolutely (4.1) receiving signal data measurements corresponding to NOT in the estimated area, 0 indicates a substantially neutral wireless communications between an MS to be located or unknown likelihood of the target MS being in the corre (herein also denoted the “target MS) and a wireless sponding estimated area, and 1 indicates that the target MS is telephony infrastructure; — absolutely within the corresponding estimated area. (4.2) organizing and processing the signal data measure Referring to (4.4) above, it is an aspect of the present ments received from a given target MS and Surrounding disclosure to provide location hypothesis enhancing and BSS so that composite wireless signal characteristic val evaluation techniques that can adjust target MS location esti ues may be obtained from which target MS location 10 mates according to historical MS location data and/or adjust estimates may be subsequently derived. In particular, the the confidence values of location hypotheses according to signal data measurements are ensembles of samples how consistent the corresponding target MS location estimate from the wireless signals received from the target MS by is: (a) with historical MS signal characteristic values, (b) with the base station infrastructure, wherein these samples various physical constraints, and (c) with various heuristics. are Subsequently filtered using analog and digital spec 15 In particular, the following capabilities are provided by the tral filtering. present disclosure: the present disclosure accomplishes the objectives mentioned (5.1) a capability for enhancing the accuracy of an initial above by the following steps: location hypothesis, H, generated by a first order model, (4.3) providing the composite signal characteristic values FOM, by using Has, essentially, a query or index into to one or more MS location hypothesizing computa an historical database (denoted herein as the location tional models (also denoted herein as “first order mod signature database), wherein this database includes: (a) els' and also “location estimating models'), wherein a plurality of previously obtained location signature each Such model Subsequently determines one or more clusters (i.e., composite wireless signal characteristic initial estimates of the location of the target MS based values) Such that for each Such cluster there is an asso on, for example, the signal processing techniques 2.1 25 ciated actual or verified MS locations where an MS through 2.3 above. Moreover, each of the models output communicated with the base station infrastructure for MS location estimates having substantially identical locating the MS, and (b) previous MS location hypoth data structures (each such data structure denoted a “loca esis estimates from FOM, derived from each of the tion hypothesis). Additionally, each location hypoth location signature clusters stored according to (a): esis may also includes a confidence value indicating the 30 (5.2) a capability for analyzing composite signal charac likelihood or probability that the targetMS whose loca teristic values of wireless communications between the tion is desired resides in a corresponding location esti target MS and the base station infrastructure, wherein mate for the target MS; Such values are compared with composite signal char (4.4) adjusting or modifying location hypotheses output by acteristics values of known MS locations (these latter the models according to, for example, 2.4 through 2.6 35 values being archived in the location signature data above so that the adjusted location hypotheses provide base). In one instance, the composite signal characteris better target MS location estimates. In particular, such tic values used to generate various location hypotheses adjustments are performed on both the target MS loca for the target MS are compared against wireless signal tion estimates of the location hypotheses as well as their data of known MS locations stored in the location sig corresponding confidences; and 40 nature data base for determining the reliability of the (4.4) Subsequently computing a “most likely target MS location hypothesizing models for particular geographic location estimate for outputting to a location requesting areas and/or environmental conditions; application Such as 911 emergency, the fire or police (5.3) a capability for reasoning about the likeliness of a departments, taxi services, etc. Note that in computing location hypothesis wherein this reasoning capability the most likely target MS location estimate a plurality of 45 uses heuristics and constraints based on physics and location hypotheses may be taken into account. In fact, it physical properties of the location geography; is an important aspect of the present disclosure that the (5.4) an hypothesis generating capability for generating most likely MS location estimate is determined by com new location hypotheses from previous hypotheses. putationally forming a composite MS location estimate As also mentioned above in (2.3), the present disclosure utilizing such a plurality of location hypotheses so that, 50 utilizes adaptive signal processing techniques. One particu for example, location estimate similarities between larly important utilization of Such techniques includes the location hypotheses can be effectively utilized. automatic tuning of the embodiments disclosed herein so that, Referring now to (4.3) above, the filtered and aggregated e.g., Such tuning can be applied to adjusting the values of wireless signal characteristic values are provided to a number location processing system parameters that affect the pro of location hypothesizing models (denoted First Order Mod 55 cessing performed by the embodiments disclosed herein. For els, or FOMs), each of which yields a location estimate or example, Such system parameters as those used for determin location hypothesis related to the location of the target MS. In ing the size of a geographical area to be specified when particular, there are location hypotheses for both providing retrieving location signal data of known MS locations from estimates of where the target MS likely to be and where the the historical (location signature) database can Substantially target MS is not likely to be. Moreover, it is an aspect of the 60 affect the location processing. In particular, a system param present disclosure that confidence values of the location eter specifying a minimum size for Such a geographical area hypotheses are provided as a continuous range of real num may, if too large, cause unnecessary inaccuracies in locating bers from, e.g., -1 to 1, wherein the most unlikely areas for an MS. Accordingly, to accomplish a tuning of Such system locating the target MS are given a confidence value of -1, and parameters, an adaptation engine is included in the for auto the most likely areas for locating the target MS are given a 65 matically adjusting ortuning parameters used by the embodi confidence value of 1. That is, confidence values that are ments disclosed herein. Note that in one embodiment, the larger indicate a higher likelihood that the target MS is in the adaptation engine is based on genetic algorithm techniques. US 9,134,398 B2 15 16 A novel aspect of the present disclosure relies on the dis a grid of such LBSs can be utilized for providing location covery that in many areas where MS location services are signal data (from the built-in MS) for (re)training or (re) desired, the wireless signal measurements obtained from calibrating such classification FOMs. communications between the target MS and the base station In one embodimentofa system and/or method according to infrastructure are extensive enough to provide Sufficiently the present disclosure, one or more classification FOMs may unique or peculiar values so that the pattern of values alone each include a learning module Such as an artificial neural may identify the location of the target MS. Further, assuming network (ANN) for associating target MS location signal data a sufficient amount of such location identifying pattern infor with a target MS location estimate. Additionally, one or more mation is captured in the composite wireless signal charac classification FOMs may be statistical prediction models teristic values for a target MS, and that there is a technique for 10 based on Such statistical techniques as, for example, principle matching such wireless signal patterns to geographical loca decomposition, partial least Squares, or other regression tech tions, then a FOM based on this technique may generate a niques. reasonably accurate target MS location estimate. Moreover, if It is a further aspect of the present disclosure that the the embodiments disclosed herein (e.g., the location signa personal communication system (PCS) infrastructures cur ture data base) has captured Sufficient wireless signal data 15 rently being developed by telecommunication providers offer from location communications between MSs and the base an appropriate localized infrastructure base upon which to station infrastructure wherein the locations of the MSs are build various personal location systems (PLS) employing a also verified and captured, then this captured data (e.g., loca system and/or method according to the present disclosure tion signatures) can be used to train or calibrate such models and/or utilizing the techniques disclosed herein. In particular, to associate the location of a target MS with the distinctive a system and/or method according to the present disclosure is signal characteristics between the target MS and one or more especially suitable for the location of people and/or objects base stations. Accordingly, the a system or method according using code division multiple access (CDMA) wireless infra to the present disclosure may include one or more FOMs that structures, although other wireless infrastructures, such as, may be generally denoted as classification models wherein time division multiple access (TDMA) infrastructures and such FOMs are trained or calibrated to associate particular 25 GSM are also contemplated. Note that CDMA personal com composite wireless signal characteristic values with a geo munications systems are described in the Telephone Indus graphical location where a target MS could likely generate the tries Association standard IS-95, for frequencies below 1 wireless signal samples from which the composite wireless GHZ, and in the Wideband Spread-Spectrum Digital Cellular signal characteristic values are derived. Further, the a system System Dual-Mode Mobile Station-Base Station Compatibil or method according to the present disclosure may include the 30 ity Standard, for frequencies in the 1.8-1.9 GHz frequency capability for training (calibrating) and retraining (recalibrat bands, both of which are incorporated herein by reference. ing) such classification FOMs to automatically maintain the Furthermore, CDMA general principles have also been accuracy of these models even though Substantial changes to described, for example, in U.S. Pat. No. 5,109,390, to Gil the radio coverage area may occur, Such as the construction of housen, etal, filed Nov. 7, 1989, and CDMA Network Engi a new high rise building or seasonal variations (due to, for 35 neering Handbook by Qualcomm, Inc., each of which is also example, foliage variations). incorporated herein by reference. Note that such classification FOMs that are trained or cali Notwithstanding the above mentioned CDMA references, brated to identify target MS locations by the wireless signal a brief introduction of CDMA is given here. Briefly, CDMA patterns produced constitute a particularly novel aspect of the is an electromagnetic signal modulation and multiple access present disclosure. It is well known in the wireless telephony 40 scheme based on spread spectrum communication. Each art that the phenomenon of signal multipath and shadow CDMA signal corresponds to an unambiguous pseudoran fading renders most analytical location computational tech dom binary sequence for modulating the carrier signal niques such as time-of-arrival (TOA) or time-difference-of throughout a predetermined spectrum of bandwidth frequen arrival (TDOA) substantially useless in urban areas and par cies. Transmissions of individual CDMA signals are selected ticularly in dense urban areas. However, this same multipath 45 by correlation processing of a pseudonoise waveform. In phenomenon also may produce Substantially distinct or pecu particular, the CDMA signals are separately detected in a liar signal measurement patterns, wherein Such a pattern coin receiver by using a correlator, which accepts only signal cides with a relatively small geographical area. Thus, a sys energy from the selected binary sequence and despreads its tem or method according to the present disclosure may spectrum. Thus, when a first CDMA signal is transmitted, the include utilizes multipath as an advantage for increasing 50 transmissions of unrelated CDMA signals correspond to accuracy where for previous location systems multipath has pseudorandom sequences that do not match the first signal. been a source of Substantial inaccuracies. Moreover, it is Therefore, these other signals contribute only to the noise and worthwhile to note that the utilization of classification FOMs represent a self-interference generated by the personal com in high multipath environments is especially advantageous in munications system. that high multipath environments are typically densely popu 55 As mentioned in the discussion of classification FOMs lated. Thus, since Such environments are also capable of above, a system and/or method according to the present dis yielding a greater density of MS location signal data from closure can Substantially automatically retrain and/or recali MSs whose actual locations can be obtained, there can be a brate itself to compensate for variations in wireless signal Substantial amount of training or calibration data captured by characteristics (e.g., multipath) due to environmental and/or a system or method according to the present disclosure may 60 topographic changes to a geographic area serviced by a sys include for training or calibrating such classification FOMs tem and/or method according to the present disclosure. For and for progressively improving the MS location accuracy of example, in one embodiment of a system and/or method Such models. Moreover, since it is also a related aspect of a according to the present disclosure there may below cost, low system or method according to the present disclosure may power base stations, denoted location base stations (LBS) include to include a plurality stationary, low cost, low power 65 above, providing, for example, CDMA pilot channels to a “location detection base stations’ (LBS), each having both very limited area about each such LBS. The location base restricted range MS detection capabilities and a built-in MS, stations may provide limited voice traffic capabilities, but US 9,134,398 B2 17 18 each is capable of gathering Sufficient wireless signal char (b) testing the performance of the modified location acteristics from an MS within the location base stations system on Verified mobile station location data (includ range to facilitate locating the MS. Thus, by positioning the ing the stationary transceiver signal characteristic data), location base stations at known locations in a geographic these steps being interleaved and repeatedly performed region Such as, for instance, on Street lamp poles and road for obtaining better system location accuracy within signs, additional MS location accuracy can be obtained. That useful time constraints. is, due to the low power signal output by Such location base It is also an aspect of the present disclosure to automati stations, for there to be signaling control communication cally (re)calibrate as in (6.3) above with signal characteristics (e.g., pilot signaling and other control signals) between a from other known or verified locations. In one embodiment of location base station and a target MS, the MS must be rela 10 the present disclosure, portable location verifying electronics tively near the location base station. Additionally, for each are provided so that when such electronics are sufficiently location base station not in communication with the target near a located target MS, the electronics: (i) detect the prox MS, it is likely that the MS is not near to this location base imity of the target MS; (ii) determine a highly reliable mea station. Thus, by utilizing information received from both surement of the location of the target MS; (iii) provide this location base stations in communication with the target MS 15 measurement to other location determining components of a and those that are not in communication with the target MS, novel wireless location system according to the present dis a system and/or method according to the present disclosure closure so that the location measurement can be associated can Substantially narrow the possible geographic areas within and archived with related signal characteristic data received which the target MS is likely to be. Further, by providing each from the target MS at the location where the location mea location base station (LBS) with a co-located stationary wire surement is performed. Thus, the use of such portable loca less transceiver (denoted a built-in MS above) having similar tion verifying electronics allows a novel wireless location functionality to an MS, the following advantages are pro system according to the present disclosure to capture and vided: utilize signal characteristic data from Verified, Substantially (6.1) assuming that the co-located base station capabilities random locations for location system calibration as in (6.3) and the stationary transceiver of an LBS are such that the base 25 above. Moreover, it is important to note that such location station capabilities and the stationary transceiver communi Verifying electronics can verify locations automatically cate with one another, the stationary transceiver can be sig wherein it is unnecessary for manual activation of a location naled by another component(s) of a novel wireless location Verifying process. system according to the present disclosure to activate ordeac One embodiment of a wireless location system and/or tivate its associated base station capability, thereby conserv 30 method according to the present disclosure may include loca ing power for the LBS that operate on a restricted power such tion verifying electronics Such as a “mobile (location) base as solar electrical power; station’ (MBS) that can be, for example, incorporated into a (6.2) the stationary transceiver of an LBS can be used for vehicle, such as an ambulance, police car, or taxi. Such a transferring target MS location information obtained by the vehicle can travel to sites having a transmitting target MS, LBS to a conventional telephony base station; 35 wherein Such sites may be randomly located and the signal (6.3) since the location of each LBS is known and can be used characteristic data from the transmitting target MS at Such a in location processing, a novel wireless location system location can consequently be archived with a verified location according to the present disclosure is able to (re)train and/or measurement performed at the site by the mobile location (re)calibrate itself in geographical areas having such LBSs. base station. Moreover, it is important to note that Such a That is, by activating each LBS stationary transceiver so that 40 mobile location base station as its name implies also includes there is signal communication between the stationary trans base station electronics for communicating with mobile sta ceiver and Surrounding base stations within range, wireless tions, though not necessarily in the manner of a conventional signal characteristic values for the location of the stationary infrastructure base station. In particular, a mobile location transceiver are obtained for each Such base station. Accord base station may only monitor signal characteristics, such as ingly, Such characteristic values can then be associated with 45 MS signal strength, from a target MS without transmitting the known location of the stationary transceiver for training signals to the target MS. Alternatively, a mobile location base and/or calibrating various of the location processing modules station can periodically be in bi-directional communication of the wireless location system such as the classification with a target MS for determining a signal time-of-arrival (or FOMs discussed above. In particular, such training and/or time-difference-of-arrival) measurement between the mobile calibrating may include: 50 location base station and the target MS. Additionally, each (i) (re)training and/or (re)calibrating FOMs: Such mobile location base station includes components for (ii) adjusting the confidence value initially assigned to a estimating the location of the mobile location base station, location hypothesis according to how accurate the gen Such mobile location base station location estimates being erating FOM is in estimating the location of the station important when the mobile location base station is used for ary transceiver using data obtained from wireless signal 55 locating a target MS Via, for example, time-of-arrival or time characteristics of signals between the stationary trans difference-of-arrival measurements as one skilled in the art ceiver and base stations with which the stationary trans will appreciate. In particular, a mobile location base station ceiver is capable of communicating; can include: (iii) automatically updating the previously mentioned his (7.1) a mobile station (MS) for both communicating with torical database (i.e., the location signature database), 60 other components of a novel wireless location system accord wherein the stored signal characteristic data for each ing to the present disclosure (such as a location processing stationary transceiver can be used for detecting environ center included in the wireless location system); mental and/or topographical changes (e.g., a newly built (7.2) a GPS receiver for determining a location of the mobile high rise or other structures capable of altering the mul location base station; tipath characteristics of a given geographical area); and 65 (7.3) a gyroscope and other dead reckoning devices; and (iv) tuning of the location system parameters, wherein the (7.4) devices for operator manual entry of a mobile location steps of: (a) modifying various system parameters and base station location. US 9,134,398 B2 19 20 Furthermore, a mobile location base station includes mod disclosure readily benefits from the distinct advantages of the ules for integrating or reconciling distinct mobile location CDMA spread spectrum scheme, namely, these advantages base station location estimates that, for example, can be include the exploitation of radio frequency spectral efficiency obtained using the components and devices of (7.1) through and isolation by (a) monitoring Voice activity, (b) manage (7.4) above. That is, location estimates for the mobile location ment of two-way power control, (c) provisioning of advanced base station may be obtained from: GPS satellite data, mobile variable-rate modems and error correcting signal encoding, location base station data provided by the location processing (d) inherent resistance to fading, (e) enhanced privacy, and (f) center, deadreckoning data obtained from the mobile location multiple “rake' digital data receivers and searcher receivers base station vehicle deadreckoning devices, and location data for correlation of signal multipaths. manually input by an operator of the mobile location base 10 At a more general level, it is an aspect of the present station. disclosure to demonstrate the utilization of various novel The location estimating system of the present disclosure computational paradigms such as: offers many advantages over existing location systems. The (8.1) providing a multiple hypothesis computational architec system of the present disclosure, for example, is readily ture (as illustrated best in FIG. 8 and/or FIG. 13) wherein the adaptable to existing wireless communication systems and 15 hypotheses are: can accurately locate people and/or objects in a cost effective (8.1.1) generated by modular independent hypothesizing manner. In particular, the present disclosure requires few, if computational models; any, modifications to commercial wireless communication (8.1.2) the models are embedded in the computational systems for implementation. Thus, existing personal commu architecture in a manner wherein the architecture allows for nication system infrastructure base stations and other com Substantial amounts of application specific processing com ponents of, for example, commercial CDMA infrastructures mon or generic to a plurality of the models to be straightfor are readily adapted to use a novel wireless location system wardly incorporated into the computational architecture; according to the present disclosure. The present disclosure (8.1.3) the computational architecture enhances the can be used to locate people and/or objects that are not in the hypotheses generated by the models both according to past line-of-sight of a wireless receiver or transmitter, can reduce 25 performance of the models and according to application spe the detrimental effects of multipath on the accuracy of the cific constraints and heuristics without requiring feedback location estimate, can potentially locate people and/or objects loops for adjusting the models; located indoors as well as outdoors, and uses a number of (8.1.4) the models are relatively easily integrated into, wireless stationary transceivers for location. A novel wireless modified and extracted from the computational architecture; location system according to the present disclosure employs 30 (8.2) providing a computational paradigm for enhancing an a number of distinctly different location computational mod initial estimated Solution to a problem by using this initial els for location which provides a greater degree of accuracy, estimated solution as, effectively, a query or index into an robustness and Versatility than is possible with existing sys historical database of previous Solution estimates and corre tems. For instance, the location models provided include not sponding actual solutions for deriving an enhanced solution only the radius-radius/TOA and TDOA techniques but also 35 estimate based on past performance of the module that gen adaptive artificial neural net techniques. Further, a novel erated the initial estimated solution. wireless location system according to the present disclosure Note that the multiple hypothesis architecture provided is able to adapt to the topography of an area in which location herein is useful in implementing Solutions in a wide range of service is desired. A novel wireless location system and/or applications. For example, the following additional applica method according to the present disclosure is also able to 40 tions are within the scope of the present disclosure: adapt to environmental changes Substantially as frequently as (9.1) document Scanning applications for transforming physi desired. Thus, a novel wireless location system and/or cal documents in to electronic forms of the documents. Note method according to the present disclosure is able to take into that in many cases the scanning of certain documents (books, account changes in the location topography overtime without publications, etc.) may have a 20% character recognition extensive manual data manipulation. Moreover, a novel wire 45 error rate. Thus, the novel computation architecture of the less location system and/or method according to the present present disclosure can be utilized by (I) providing a plurality disclosure can be utilized with varying amounts of signal of document scanning models as the first order models, (ii) measurement inputs. Thus, if a location estimate is desired in building a character recognition data base for archiving a a very short time interval (e.g., less than approximately one to correspondence between characteristics of actual printed two seconds), then the present location estimating system can 50 character variations and the intended characters (according be used with only as much signal measurement data as is to, for example, font types), and additionally archiving a possible to acquire during an initial portion of this time inter correspondence of performance of each of the models on val. Subsequently, after a greater amount of signal measure previously encountered actual printed character variations ment data has been acquired, additional more accurate loca (note, this is analogous to the Signature Data Base of the MS tion estimates may be obtained. Note that this capability can 55 location application described herein), and (iii) determining be useful in the context of 911 emergency response in that a any generic constraints and/or heuristics that are desirable to first quick coarse wireless mobile station location estimate be satisfied by a plurality of the models. Accordingly, by can be used to routea 911 call from the mobile station to a 911 comparing outputs from the first order document scanning emergency response center that has responsibility for the area models, a determination can be made as to whether further containing the mobile station and the 911 caller. Subse 60 processing is desirable due to, for example, discrepancies quently, once the 911 call has been routed according to this between the output of the models. If further processing is first quick location estimate, by continuing to receive addi desirable, then an embodiment of the multiple hypothesis tional wireless signal measurements, more reliable and accu architecture provided herein may be utilized to correct such rate location estimates of the mobile station can be obtained. discrepancies. Note that in comparing outputs from the first Moreover, there are numerous additional advantages of the 65 order document Scanning models, these outputs may be com system of the present disclosure when applied in CDMA pared at various granularities; e.g., character, sentence, para communication systems. The location system of the present graph or page; US 9,134,398 B2 21 22 (9.2) diagnosis and monitoring applications such as medical Note that in some embodiments of the present disclosure, diagnosis/monitoring, communication network diagnosis/ since there is a lack of sequencing between the FOMs and monitoring; Subsequent processing of location hypotheses, the FOMs can (9.3) robotics applications such as scene and/or object recog be incorporated into an expert system, if desired. For nition; 5 example, each FOM may be activated from an antecedent of (9.4) seismic and/or geologic signal processing applications an expert System rule. Thus, the antecedent for Such a rule can Such as for locating oil and gas deposits; evaluate to TRUE if the FOM outputs a location hypothesis, (9.5) Additionally, note that this architecture need not have all and the consequent portion of such a rule may put the output modules co-located. In particular, it is an additional aspect of location hypothesis on a list of location hypotheses occurring the present disclosure that various modules can be remotely 10 in a particular time window for Subsequent processing by the located from one another and communicate with one another location center. Alternatively, activation of the FOMs may be via telecommunication transmissions such as telephony tech in the consequents of Such expert System rules. That is, the nologies and/or the Internet. Accordingly, the present disclo antecedent of such an expert System rule may determine if the Sure is particularly adaptable to such distributed computing 15 conditions are appropriate for invoking the FOMCs) in the environments. For example, some number of the first order rules consequent. models may reside in remote locations and communicate Of course, other software architectures may also be used in their generated hypotheses via the Internet. implementing the processing of the location center without For instance, in weather prediction applications it is not departing from Scope of the present disclosure. In particular, uncommon for computational models to require large object-oriented architectures are also within the scope of the amounts of computational resources. Thus, such models run present disclosure. For example, the FOMs may be object ning at various remote computational facilities can transfer methods on an MS location estimator object, wherein the weather prediction hypotheses (e.g., the likely path of a hur estimator object receives substantially all target MS location ricane) to a site that performs hypothesis adjustments accord signal data output by the signal filtering Subsystem. Alterna ing to: (i) past performance of the each model; (ii) particular 25 tively, software bus architectures are contemplated by the constraints and/or heuristics, and Subsequently outputs a present disclosure, as one skilled in the art will understand, most likely estimate for a particular weather condition. wherein the software architecture may be modular and facili In an alternative embodiment of the present disclosure, the tate parallel processing. processing following the generation of location hypotheses Further features and advantages of the present disclosure (each having an initial location estimate) by the first order 30 are provided by the figures and detailed description accom models may be such that this processing can be provided on panying this Summary Section. Internet user nodes and the first order models may reside at Internet server sites. In this configuration, an Internet user BRIEF DESCRIPTION OF THE DRAWINGS may request hypotheses from Such remote first order models and perform the remaining processing at his/her node. 35 FIG. 1 illustrates various perspectives of radio propagation In other embodiments of the present disclosure, a fast, opportunities which may be considered in addressing corre albeit less accurate location estimate may be initially per lation with mobile to base station ranging. formed for very time critical location applications where FIG. 2 shows aspects of the two-ray radio propagation approximate location information may be required. For model and the effects of urban clutter. example, less than 1 Second response for a mobile station 40 FIG. 3 provides a typical example of how the statistical location embodiment of the present disclosure may be desired power budget is calculated in design of a Commercial Mobile for 911 emergency response location requests. Subsequently, Radio Service Provider (CMRS) network. once a relatively coarse location estimate has been provided, FIG. 4 illustrates an overall view of a wireless radio loca a more accurate most likely location estimate can be per tion network architecture, based on AIN principles. formed by repeating the location estimation processing a 45 FIG. 5 is a high level block diagram of an embodiment of second time with, e.g., additional with measurements of wire a novel wireless location system according to the present less signals transmitted between a mobile station to be located disclosure for locating a mobile station (MS) within a corre and a network of base stations with which the mobile station sponding radio coverage area. is communicating, thus providing a second, more accurate FIG. 6 is a high level block diagram of the location center location estimate of the mobile station. 50 142. Additionally, note that it is within the scope of the present FIG. 7 is a high level block diagram of the hypothesis disclosure to provide one or more central location develop evaluator for the location center. ment sites that may be networked to, for example, geographi FIG. 8 is a substantially comprehensive high level block cally dispersed location centers providing location services diagram illustrating data and control flows between the com according to the present disclosure, wherein the FOMs may 55 ponents of the location center, as well the functionality of the be accessed. Substituted, enhanced or removed dynamically components. via network connections (via, e.g., the Internet) with a central FIGS. 9A and 9B is a high level data structure diagram location development site. Thus, a small but rapidly growing describing the fields of a location hypothesis object generated municipality in Substantially flat low density area might ini by the first order models 1224 of the location center. tially be provided with access to, for example, two or three 60 FIG. 10 is a graphical illustration of the computation per FOMs for generating location hypotheses in the municipali formed by the most likelihood estimator 1344 of the hypoth ty's relatively uncluttered radio signaling environment. How esis evaluator. ever, as the population density increases and the radio signal FIG. 11 is a high level block diagram of the mobile base ing environment becomes cluttered by, for example, thermal station (MBS). noise and multipath, additional or alternative FOMs may be 65 FIG. 12 is a high level state transition diagram describing transferred via the network to the location center for the computational states the Mobile Base station enters during municipality. operation. US 9,134,398 B2 23 24 FIG. 13 is a high level diagram illustrating the data struc FIGS. 27a through 27b present a high level flowchart of the tural organization of the Mobile Base station capability for steps performed by the function, “CONFIDENCE AD autonomously determining a most likely MBS location from JUSTER,” used in the context adjuster 1326 for adjusting a plurality of potentially conflicting MBS location estimating mobile station estimates provided by the first order models SOUCS. 1224; this flowchart corresponds to the description of this FIG. 14 shows one method of modeling CDMA delay function in APPENDIX D. spread measurement ensembles and interfacing such signals FIGS. 28a and 28b presents a high level flowchart of the to a typical artificial neural network based FOM. steps performed by the function, “GET COMPOSITE PRE FIG. 15 illustrates the nature of RF “Dead Zones', notch DICTION MAPPED CLUSTER DENSITY” used in the area, and the importance of including location data signatures 10 context adjuster 1326 for adjusting mobile station estimates from the back side of radiating elements. provided by the first order models 1224; this flowchart cor FIGS. 16a through 16c present a table providing a brief responds to the description of this function in APPENDIX D. description of the attributes of the location signature data type FIGS. 29a through 29h presenta high level flowchart of the stored in the location signature database 1320. steps performed by the function, “GET PREDIC FIGS. 17a through 17c present a high level flowchart of the 15 TION MAPPED CLUSTER DENSITY FOR, used in steps performed by function, “UPDATE LOC SIG DB.” the context adjuster 1326 for adjusting mobile station esti for updating location signatures in the location signature data mates provided by the first order models 1224; this flowchart base 1320; note, this flowchart corresponds to the description corresponds to the description of this function in APPENDIX of this function in APPENDIX C. D. FIGS.18a through 18b present a high level flowchart of the FIG. 30 illustrates the primary components of the signal steps performed by function, “REDUCE BAD DB LOC processing Subsystem. SIGS. for updating location signatures in the location signa FIG. 31 illustrates how automatic provisioning of mobile ture database 1320; note, this flowchart corresponds to the station information from multiple CMRS occurs. description of this function in APPENDIX C. FIGS. 19a through 19bpresent a high level flowchart of the 25 DETAILED DESCRIPTION steps performed by function, “INCREASE CONFIDEN CE OF GOOD DB LOC SIGS.” for updating location Detailed Description Introduction signatures in the location signature database 1320; note, this flowchart corresponds to the description of this function in Various digital wireless communication standards have been APPENDIX C. 30 introduced such as Advanced Mobile PhoneService (AMPS), FIGS.20a through 20d present a high level flowchart of the Narrowband Advanced Mobile Phone Service (NAMPS), steps performed by function, “DETERMINE LOCATION code division multiple access (CDMA) and Time Division SIGNATURE FIT ERRORS,” for updating location signa Multiple Access (TDMA) (e.g., Global Systems Mobile tures in the location signature data base 1320; note, this (GSM). These standards provide numerous enhancements for flowchart corresponds to the description of this function in 35 advancing the quality and communication capacity for wire APPENDIX C. less applications. Referring to CDMA, this standard is FIG. 21 presents a high level flowchart of the steps per described in the Telephone Industries Association standard formed by function, “ESTIMATE LOC SIG FROM DB.” IS-95, for frequencies below 1 GHz, and in J-STD-008, the for updating location signatures in the location signature data Wideband Spread-Spectrum Digital Cellular System Dual base 1320; note, this flowchart corresponds to the description 40 Mode Mobile Station-Base station Compatibility Standard, of this function in APPENDIX C. for frequencies in the 1.8-1.9 GHz frequency bands. Addi FIGS. 22a through 22b present a high level flowchart of the tionally, CDMA general principles have been described, for steps performed by function, "GET AREA TO SEARCH.” example, in U.S. Pat. No. 5,109,390, Diversity Receiver in a for updating location signatures in the location signature data CDMA Cellular Telephone System by Gilhousen. There are base 1320; note, this flowchart corresponds to the description 45 numerous advantages of Such digital wireless technologies of this function in APPENDIX C. such as CDMA radio technology. For example, the CDMA FIGS. 23a through 23c present a high level flowchart of the spread spectrum scheme exploits radio frequency spectral steps performed by function, “GET DIFFERENCE MEA efficiency and isolation by monitoring voice activity, manag SUREMENT' for updating location signatures in the loca ing two-way power control, provision of advanced variable tion signature data base 1320; note, this flowchart corre 50 rate modems and error correcting signal design, and includes sponds to the description of this function in APPENDIX C. inherent resistance to fading, enhanced privacy, and provides FIG. 24 is a high level illustration of context adjuster data for multiple “rake' digital data receivers and searcher receiv structures and their relationship to the radio coverage area for ers for correlation of multiple physical propagation paths, a novel wireless location system according to the present resembling maximum likelihood detection, as well as Support disclosure; 55 for multiple base station communication with a mobile sta FIGS.25a through 25b present a high level flowchart of the tion, i.e., soft or softer hand-off capability. When coupled steps performed by the function, “CONTEXT ADJUSTER,” with a location center as described herein, substantial used in the context adjuster 1326 for adjusting mobile station improvements in radio location can be achieved. For estimates provided by the first order models 1224; this flow example, the CDMA spread spectrum scheme exploits radio chart corresponds to the description of this function in 60 frequency spectral efficiency and isolation by monitoring APPENDIX D. Voice activity, managing two-way power control, provision of FIGS. 26a through 26c present a high level flowchart of the advanced variable-rate modems and error correcting signal steps performed by the function, “GET ADJUSTED LOC design, and includes inherent resistance to fading, enhanced HYP LIST FOR,” used in the context adjuster 1326 for privacy, and provides for multiple “rake' digital data receiv adjusting mobile station estimates provided by the first order 65 ers and searcher receivers for correlation of multiple physical models 1224; this flowchart corresponds to the description of propagation paths, resembling maximum likelihood detec this function in APPENDIX D. tion, as well as Support for multiple base station communica US 9,134,398 B2 25 26 tion with a mobile station, i.e., soft hand-off capability. More In operation, the MS 140 may utilize one of the wireless over, this same advanced radio communication infrastructure technologies, CDMA, TDMA, AMPS, NAMPS or GSM can also be used for enhanced radio location. As a further techniques for radio communication with: (a) one or more example, the capabilities of IS-41 and AIN already provide a infrastructure base stations 122, (b) mobile base station(s) broad-granularity of wireless location, as is necessary to, for 148, (c) an LBS 152. example, properly direct a terminating call to an MS. Such Referring to FIG. 4 again, additional detail is provided of information, originally intended for call processing usage, typical base station coverage areas, sectorization, and high can be re-used in conjunction with the location center level components within a radio coverage area 120, including described hereinto provide wireless location in the large (i.e., the MSC 112. Although base stations may be placed in any to determine which country, state and city a particular MS is 10 configuration, a typical deployment configuration is approxi located) and wireless location in the Small (i.e., which loca mately in a cellular honeycomb pattern, although many prac tion, plus or minus a few hundred feet within one or more base tical tradeoffs exist, such as site availability, versus the stations a given MS is located). requirement for maximal terrain coverage area. To illustrate, FIG. 4 is a high level diagram of a wireless digital radiolo three such exemplary base stations (BSs) are 122A, 122B and cation intelligent network architecture for a novel wireless 15 122C, each of which radiate referencing signals within their location system according to the present disclosure. Accord area of coverage 169 to facilitate mobile station (MS) 140 ingly, this figure illustrates the interconnections between the radio frequency connectivity, and various timing and Syn components, for example, of a typical PCS network configu chronization functions. Note that some base stations may ration and various components that are specific to an embodi contain no sectors 130 (e.g. 122E), thus radiating and receiv ment of all wireless location system according to the present ing signals in a 360 degree omnidirectional coverage area disclosure. In particular, as one skilled in the art will under pattern, or the base station may contain "Smart antennas' stand, a typical wireless (PCS) network includes: which have specialized coverage area patterns. However, the (a) a (large) plurality of conventional wireless mobile sta generally most frequent base stations 122 have three sector tions (MSs) 140 for at least one of voice related com 130 coverage area patterns. For example, base station 122A munication, visual (e.g., text) related communication, 25 includes sectors 130, additionally labeled a, b and c. Accord and according to present invention, location related ingly, each of the sectors 130 radiate and receive signals in an communication; approximate 120 degree arc, from an overhead view. As one (b) a mobile switching center (MSC) 112: skilled in the art will understand, actual base station coverage (c) a plurality of wireless cell sites in a radio coverage area areas 169 (stylistically represented by hexagons about the 120, wherein each cell site includes an infrastructure 30 base stations 122) generally are designed to overlap to some base station such as those labeled 122 (or variations extent, thus ensuring seamless coverage in a geographical thereof such as 122A-122D). In particular, the base sta area. Control electronics within each base station 122 are tions 122 denote fixed location base stations used for used to communicate with a mobile stations 140. Information voice and data communication with a plurality of MSs regarding the coverage area for each sector 130, Such as its 140, and which are also used for communication of 35 range, area, and “holes' or areas of no coverage (within the information related to locating such MSs 140. Addition radio coverage area 120), may be known and used by the ally, note that the base stations labeled 152 are more location center 142 to facilitate location determination. Fur directly related to wireless location enablement. For ther, during communication with a mobile station 140, the example, as described in greater detail hereinbelow, the identification of each base station 122 communicating with base stations 152 may be low cost, low functionality 40 the MS 140 as well, as any sector identification information, transponders that are used primarily in communicating may be known and provided to the location center 142. MS location related information to the location center In the case of the base station types 122, 148, and 152 142 (via base stations 122 and the MSC 112). Note that communication of location information, a base station or unless stated otherwise, the base stations 152 will be mobility controller 174 (BSC) controls, processes and pro referred to hereinafter as “location base station(s) 152 45 vides an interface between originating and terminating tele or simply “LBS(s) 152'); phone calls from/to mobile station (MS) 140, and the mobile (d) a public switched telephone network (PSTN) 124 switch center (MSC) 112. The MSC 122, on-the-other-hand, (which may include signaling system links 106 having performs various administration functions such as mobile network control components such as: a service control station 140 registration, authentication and the relaying of point (SCP) 104, one or more signaling transfer points 50 various system parameters, as one skilled in the art will under (STPs) 110. stand. Added to this wireless network, the following additional The base stations 122 may be coupled by various transport components are provided: facilities 176 such as leased lines, frame relay, T-Carrier links, (10.1) a location center 142 which is required for determining optical fiber links or by microwave communication links. a location of a target MS 140 using signal characteristic 55 When a mobile station 140 (such as a CDMA, AMPS, values for this target MS; NAMPS mobile telephone) is powered on and in the idle (10.2) one or more mobile base stations 148 (MBS) which are state, it constantly monitors the pilot signal transmissions optional, for physically traveling toward the target MS 140 or from each of the base stations 122 located at nearby cell sites. tracking the target MS; Since base station/sector coverage areas may often overlap, (10.3) a plurality of location base stations 152 (LBS) which 60 Such overlapping enables mobile stations 140 to detect, and, are optional, distributed within the radio coverage areas 120, in the case of certain wireless technologies, communicate each LBS 152 having a relatively small MS 140 detection area simultaneously along both the forward and reverse paths, 154; with multiple base stations 122 and/or sectors 130. In FIG. 4 Since location base stations can be located on potentially the constantly radiating pilot signals from base station sectors each floor of a multi-story building, the wireless location 65 130, such as sectors a, b and c of BS 122A, are detectable by technology described herein can be used to perform location mobile stations 140 within the coverage area 169 for BS in terms of height as well as by latitude and longitude. 122A. That is, the mobile stations 140 scan for pilot channels, US 9,134,398 B2 27 28 corresponding to a given base station/sector identifiers (IDS). 140. The computing and display provides a means for com for determining which coverage area 169 (i.e., cell) it is municating the position of the target MS 140 on a map display contained. This is performed by comparing signals strengths to an operator of the MBS 148. of pilot signals transmitted from these particular cell-sites. Each location base station (LBS) 152 is a low cost location The mobile station 140 then initiates a registration request device. Each such LBS 152 communicates with one or more with the MSC 112, via the base station controller 174. The of the infrastructure base stations 122 using one or more MSC 112 determines whether or not the mobile station 140 is wireless technology interface standards. In some embodi allowed to proceed with the registration process (except in the ments, to provide such LBS's cost effectively, each LBS 152 case of a 911 call, wherein no registration process is only partially or minimally Supports the air-interface stan required). At this point calls may be originated from the 10 dards of the one or more wireless technologies used in com mobile station 140 or calls or short message service messages municating with both the BSs 122 and the MSs 140. Each can be received from the network. The MSC 112 communi LBS 152, when put in service, is placed at a fixed location, cates as appropriate, with a class 4/5 wireline telephony cir Such as at a traffic signal, lamp post, etc., and wherein the cuit switch or other central offices, connected to the PSTN location of the LBS may be determined as accurately as, for 124 network. Such central offices connect to wireline termi 15 example, the accuracy of the locations of the infrastructure nals, such as telephones, or any communication device com BSS 122. Assuming the wireless technology CDMA is used, patible with the line. The PSTN 124 may also provide con each BS 122 uses a time offset of the pilot PN sequence to nections to long distance networks and other networks. identify a forward CDMA pilot channel. In one embodiment, The MSC 112 may also utilize IS/41 data circuits or trunks each LBS 152 emits a unique, time-offset pilot PN sequence connecting to signal transfer point 110, which in turn con channel in accordance with the CDMA standard in the RF nects to a service control point 104, via Signaling System #7 spectrum designated for BSs 122, such that the channel does (SS7) signaling links (e.g., trunks) for intelligent call process not interfere with neighboring BSs 122 cell site channels, nor ing, as one skilled in the art will understand. In the case of would it interfere with neighboring LBSs 152. However, as wireless AIN services such links are used for call routing one skilled in the art will understand, time offsets, in CDMA instructions of calls interacting with the MSC 112 or any 25 chip sizes, may be re-used within a PCS system, thus provid Switch capable of providing service Switching point func ing efficient use of pilot time offset chips, thereby achieving tions, and the public switched telephone network (PSTN) spectrum efficiency. Each LBS 152 may also contain multiple 124, with possible termination back to the wireless network. wireless receivers in order to monitor transmissions from a Referring to FIG. 4 again, the location center (LC) 142 target MS 140. Additionally, each LBS 152 contains mobile interfaces with the MSC 112 either via dedicated transport 30 station 140 electronics, thereby allowing the LBS to both be facilities 178, using for example, any number of LAN/WAN controlled by the LC 142, and to transmit information to the technologies, such as Ethernet, fast Ethernet, frame relay, LC 142, via at least one neighboring BS 122. virtual private networks, etc., or via the PSTN 124. The LC As mentioned above, when the location of a particular 142 receives autonomous (e.g., unsolicited) command/re target MS 140 is desired, the LC 142 can request location sponse messages regarding, for example: (a) the state of the 35 information about the target MS 140 from, for instance, one wireless network of each service provider, (b) MS 140 and BS or more activated LBSs 152 in a geographical area of interest. 122 radio frequency (RF) measurements, (c) any MBSs 148, Accordingly, whenever the target MS 140 is in such an area, (d) location applications requesting MS locations using the or is Suspected of being in the area, either upon command location center. Conversely, the LC 142 provides data and from the LC 142, or in a substantially continuous fashion, the control information to each of the above components in (a)- 40 LBS’s pilot channel appears to the target MS 140 as a poten (d). Additionally, the LC 142 may provide location informa tial neighboring base station channel, and consequently, is tion to an MS 140, via a BS 122. Moreover, in the case of the placed, for example, in the CDMA neighboring set, or the use of a mobile base station (MBS) 148, several communica CDMA remaining set, of the target MS 140 (as one familiar tions paths may exist with the LC 142. with the CDMA standards will understand). The MBS 148 acts as a low cost, partially-functional, mov 45 During the normal CDMA pilot search sequence of the ing base station, and is, in one embodiment, situated in a mobile station initialization state (in the targetMS), the target vehicle where an operator may engage in MS 140 searching MS 140 will, if within range of such an activated LBS 152, and tracking activities. In providing these activities using detect the LBS pilot presence during the CDMA pilot channel CDMA, the MBS 148 provides a forward link pilot channel acquisition substrate. Consequently, the target MS 140 per for a target MS 140, and subsequently receives unique BS 50 forms RF measurements on the signal from each detected pilot strength measurements from the MS 140. The MBS 148 LBS 152. Similarly, an activated LBS 152 can perform RF also includes a mobile station for data communication with measurements on the wireless signals from the target MS 140. the LC 142, via a BS 122. In particular, such data communi Accordingly, each LBS 152 detecting the target MS 140 may cation includes telemetering the geographic position of the subsequently telemeter back to the LC 142 measurement MBS 148 as well as various RF measurements related to 55 results related to signals from/to the target MS 140. More signals received from the target MS 140. In some embodi over, upon command, the target MS 140 will telemeter back ments, the MBS 148 may also utilize multiple-beam fixed to the LC 142 its own measurements of the detected LBSs antenna array elements and/or a moveable narrow beam 152, and consequently, this new location information, in con antenna, such as a microwave dish 182. The antennas for Such junction with location related information received from the embodiments may have a known orientation in order to fur 60 BSS 122, can be used to locate the target MS 140. ther deduce a radio location of the target MS 140 with respect It should be noted that an LBS 152 will normally deny to an estimated current location of the MBS 148. As will be hand-off requests, since typically the LBS does not require described in more detail herein below, the MBS 148 may the added complexity of handling voice or traffic bearer chan further contain a global positioning system (GPS), distance nels, although economics and peak traffic load conditions sensors, deadreckoning electronics, as well as an on-board 65 would dictate preference here. GPS timing information, computing system and display devices for locating both the needed by any CDMA base station, is either achieved via the MBS 148 itself as well as tracking and locating the target MS inclusion of a local GPS receiver or via a telemetry process US 9,134,398 B2 29 30 from a neighboring conventional BS 122, which contains a mobile station contains a sufficient number of data receivers. GPS receiver and timing information. Since energy require Although traditional TOA and TDOA methods would discard ments are minimal in such an LBS 152, (rechargeable) bat Subsequent fingers related to the same transmitted finger, teries or solar cells may be used to power the LBS. No expen collection and use of these additional values can prove useful sive terrestrial transport link is typically required since two to reduce location ambiguity, and are thus collected by the way communication is provided by the included MS 140 (or Signal Processing Subsystem in the Location Center 142. an electronic variation thereof). From the mobile receiver's perspective, a number of com Thus, LBSs 152 may be placed in numerous locations, binations of measurements could be made available to the Such as: Location Center. Due to the disperse and near-random nature (a) in dense urban canyon areas (e.g., where signal recep 10 of CDMA radio signals and propagation characteristics, tra tion may be poor and/or very noisy); ditional TOA/TDOA location methods have failed in the past, (b) in remote areas (e.g., hiking, camping and skiing areas); because the number of signals received in different locations (c) along highways (e.g., for emergency as well as moni are different. In a particularly Small urban area, of say less toring traffic flow), and their rest stations; or than 500 square feet, the number of RF signals and their (d) in general, wherever more location precision is required 15 multipath components may vary by over 100 percent. than is obtainable using other wireless infrastructure Due to the large capital outlay costs associated with pro network components. viding three or more overlapping base station coverage sig Location Center Network Elements API Description nals in every possible location, most practical digital PCS A location application programming interface or L-API 14 deployments result in fewer than three base station pilot chan (see FIG. 30, and including L-API-Loc APP 135, L-API nels being reportable in the majority of location areas, thus MSC 136, and L-API-SCP 137 shown in FIG. 4), is required resulting in a larger, more amorphous location estimate. This between the location center 142 (LC) and the mobile switch consequence requires a family of location estimate location center (MSC) network element type, in order to send and modules, each firing whenever Suitable data has been pre receive various control, signals and data messages. The sented to a model, thus providing a location estimate to a L-API 14 should be implemented using a preferably high 25 backend Subsystem which resolves ambiguities. capacity physical layer communications interface, such as In one embodiment of this invention using backend IEEE standard 802.3 (10 baseT Ethernet), although other hypothesis resolution, by utilizing existing knowledge con physical layer interfaces could be used, such as fiber optic cerning base station coverage area boundaries (such as via the ATM, frame relay, etc. Two forms of API implementation are compilation a RF coverage database—either via RF coverage possible. In the first case the signals control and data mes 30 area simulations or field tests), the location error space is sages are realized using the MSC 112 vendor's native opera decreased. Negative logic Venn diagrams can be generated tions messages inherent in the product offering, without any which deductively rule out certain location estimate hypoth special modifications. In the second case the L-API includes CSS. a full Suite of commands and messaging content specifically Although the forward link mobile stations received rela optimized for wireless location purposes, which may require 35 tive signal strength (RRSSs) of detected nearby base station some, although minor development on the part of the MSC transmitter signals can be used directly by the location esti vendor. mate modules, the CDMA base stations reverse link received Signal Processor Description relative signal strength (RRSS) of the detected mobile Referring to FIG.30, the signal processing subsystem 1220 station transmitter signal must be modified prior to location receives control messages and signal measurements and 40 estimate model use, since the mobile station transmitter transmits appropriate control messages to the wireless net power level changes nearly continuously, and would thus work via the location applications programming interface render relative signal strength useless for location purposes. referenced earlier, for wireless location purposes. The signal One adjustment variable and one factor value are required processing Subsystem additionally provides various signal by the signal processing subsystem in the CDMA air interface identification, conditioning and pre-processing functions, 45 case: (1) instantaneous relative power level in dBm (IRPL) of including buffering, signal type classification, signal filtering, the mobile station transmitter, and (2) the mobile station message control and routing functions to the location esti Power Class. By adding the IRPL to the RRSSs a synthetic mate modules. relative signal strength (SRSS) of the mobile station 140 There can be several combinations of Delay Spread/Signal signal detected at the BS 122 is derived, which can be used by Strength sets of measurements made available to the signal 50 location estimate model analysis, as shown below: processing Subsystem 1220. In some cases the mobile station 140 (FIG. 4) may be able to detect up to three or four Pilot SRSS-RRSS+IRPL (in dBm) Channels representing three to four Base Stations, or as few as SRSSs, a corrected indication of the effective path loss in one Pilot Channel, depending upon the environment. Simi the reverse direction (mobile station to BS), is now compa larly, possibly more than one BS 122 can detect a mobile 55 rable with RRSSs and can be used to provide a correlation station 140 transmitter signal, as evidenced by the provision with either distance or shadow fading because it now of cell diversity or soft hand-off in the CDMA standards, and accounts for the change of the mobile station transmitter's the fact that multiple CMRS base station equipment com power level. The two signals RRSSs and SRSSs can now monly will overlap coverage areas. For each mobile station be processed in a variety of ways to achieve a more robust 140 or BS 122 transmitted signal detected by a receivergroup 60 correlation with distance or shadow fading. at a station, multiple delayed signals, or "fingers' may be Although Rayleigh fading appears as a generally random detected and tracked resulting from multipath radio propaga noise generator, essentially destroying the correlation value tion conditions, from a given transmitter. of either RRSS or SRSS measurements with distance In typical spread spectrum diversity CDMA receiver individually, several mathematical operations or signal pro design, the “first finger represents the most direct, or least 65 cessing functions can be performed on each measurement to delayed multipath signal. Second or possibly third or fourth derive a more robust relative signal strength value, overcom fingers may also be detected and tracked, assuming the ing the adverse Rayleigh fading effects. Examples include US 9,134,398 B2 31 32 averaging, taking the strongest value and weighting the stron pilot channels and the strongest first three fingers, are col gest value with a greater coefficient than the weaker value, lected and processed. From the BS 122 perspective, it is then averaging the results. This signal processing technique preferred that the strongest first four CDMA delay spread takes advantage of the fact that although a Rayleigh fade may fingers and the mobile station power level be collected and often exist in either the forward or reverse path, it is much less 5 sent to the location system 42, for each of preferably three probable that a Rayleigh fade also exists in the reverse or BSS 122 which can detect the mobile station 140. A much forward path, respectively. A shadow fade however, similarly larger combination of measurements is potentially feasible affects the signal strength in both paths. using the extended data collection capability of the CDMA At this point a CDMA radio signal direction independent receivers. of “net relative signal strength measurement can be derived 10 FIG.30 illustrates the components of the Signal Processing which can be used to establish a correlation with either dis Subsystem 1220 (also shown in FIGS. 5, 6 and 8). The main tance or shadow fading, or both. Although the ambiguity of components consist of the input queue(s)7, signal classifier/ either shadow fading or distance cannot be determined, other filter 9, digital signaling processor 17, imaging filters 19, means can be used in conjunction, such as the fingers of the output queue(s) 21, router/distributor 23 (also denoted as the CDMA delay spread measurement, and any other TOA/ 15 “Data Capture And Gateway in FIG. 8(2)), a signal proces TDOA calculations from other geographical points. In the Sor database 26 and a signal processing controller 15. case of a mobile station with a certain amount of shadow Input queues 7 are required in order to stage the rapid fading between its BS 122 (FIG. 2), the first finger of a acceptance of a significant amount of RF signal measurement CDMA delay spread signal is most likely to be a relatively data, used for either location estimate purposes or to accept shorter duration than the case where the mobile station 140 autonomous location data. Each location request using fixed and BS 122 are separated by a greater distance, since shadow base stations may, in one embodiment, contain from 1 to 128 fading does not materially affect the arrival time delay of the radio frequency measurements from the mobile station, radio signal. which translates to approximately 61.44 kilobytes of signal By performing a small modification in the control electron measurement data to be collected within 10 seconds and 128 ics of the CDMA base station and mobile station receiver 25 measurements from each of possibly four base stations, or circuitry, it is possible to provide the signal processing Sub 245.76 kilobytes for all base stations, for a total of approxi system 1220 (reference FIG. 30) within the location center mately 640 signal measurements from the five sources, or 142 (FIG. 1) with data that exceed the one-to-one CDMA 3.07.2 kilobytes to arrive per mobile station location request in delay-spread fingers to data receiver correspondence. Such 10 seconds. An input queue Storage space is assigned at the additional information, in the form of additional CDMA fin 30 moment a location request begins, in order to establish a gers (additional multipath) and all associated detectable pilot formatted data structure in persistent store. Depending upon channels, provides new information which is used to enhance the urgency of the time required to render a location estimate, the accuracy of the location center's location estimating mod fewer or more signal measurement samples can be taken and ules. stored in the input queue(s) 7 accordingly. This enhanced capability is provided via a control mes 35 The signal processing Subsystem 1220 Supports a variety of sage, sent from the location center 142 to the mobile switch wireless network signaling measurement capabilities by center 12, and then to the base station(s) in communication detecting the capabilities of the mobile and base station with, or in close proximity with, mobile stations 140 to be through messaging structures provided by the location appli located. Two types of location measurement request control cation programming interface (L-API 14, FIG.30). Detection messages are needed: one to instruct a target mobile station 40 is accomplished in the signal classifier 9 (FIG. 30) by refer 140 (i.e., the mobile station to be located) to telemeter its BS encing a mobile station database table within the signal pro pilot channel measurements back to the primary BS 122 and cessor database 26, which provides, given a mobile station from there to the mobile switch center 112 and then to the identification number, mobile station revision code, other location system 42. The second control message is sent from mobile station characteristics. Similarly, a mobile switch cen the location system 42 to the mobile switch center 112, then 45 ter table 31 provides MSC characteristics and identifications to first the primary BS, instructing the primary BS’s searcher to the signal classifier/filter 9. The signal classifier/filter adds receiver to output (i.e., return to the initiating request message additional message header information that further classifies source) the detected target mobile station 140 transmitter the measurement data which allows the digital signal proces CDMA pilot channel offset signal and their corresponding sor and image filter components to select the proper internal delay spread finger (peak) values and related relative signal 50 processing Subcomponents to perform operations on the sig strengths. nal measurement data, for use by the location estimate mod The control messages are implemented in standard mobile ules. station 140 and BS 122 CDMA receivers such that all data Regarding service control point messages (of L-API-SCP results from the search receiver and multiplexed results from interface 137, FIG. 4) autonomously received from the input the associated data receivers are available for transmission 55 queue 7 (FIGS. 30 and 31), the signal classifier/filter 9 deter back to the location center 142. Appropriate value ranges are mines, via a signal processing database 26 query, whether required regarding mobile station 140 parameters T ADD, Such a message is to be associated with a home base station T DROP, and the ranges and values for the Active, Neigh module. Thus appropriate header information is added to the boring and Remaining Pilot sets registers, held within the message, thus enabling the message to pass through the digi mobile station 140 memory. Further mobile station 140 60 tal signal processor 17 unaffected to the output queue 21, and receiver details have been discussed above. then to the router/distributor 23. The router/distributor 23 In the normal case without any specific multiplexing means then routes the message to the HBS first order model. Those to provide location measurements, exactly how many CDMA skilled in the art will understand that associating location pilot channels and delay spread fingers can or should be requests from Home Base Station configurations require Sub measured vary according to the number of data receivers 65 stantially less data: the mobile identification number and the contained in each mobile station 140. As a guide, it is pre associated wireline telephone number transmission from the ferred that whenever RF characteristics permit, at least three home location register are on the order of less than 32 bytes. US 9,134,398 B2 33 34 Consequentially the home base station message type could be mobile stations can detect other base station (sector) pilot routed without any digital signal processing. channels which may exceed the “hop' distance, yet are nev Output queue(s) 21 (FIG. 30) are required for similar rea ertheless candidate base stations (or sectors) for wireless Sons as input queues 7: relatively large amounts of data must location purposes. Although cellular and digital cell design be held in a specific format for further location processing by may vary, “hop' distance is usually one or two cell coverage the location estimate modules 1224. areas away from the primary base station's cell coverage area. The router and distributor component 23 (FIG. 30) is Having determined a likely set of base stations which may responsible for directing specific signal measurement data both detect the mobile stations transmitter signal, as well as types and structures to their appropriate modules. For to determine the set of likely pilot channels (i.e., base stations example, the HBS FOM has no use for digital filtering struc 10 tures, whereas the TDOA module would not be able to pro and their associated physical antenna sectors) detectable by cess an HBS response message. the mobile station in the area Surrounding the primary base The controller 15 (FIG. 30) is responsible for staging the station (sector), the controller 15 initiates messages to both movement of data among the signal processing Subsystem the mobile station and appropriate base stations (sectors) to 1220 components input queue 7, digital signal processor 17, 15 perform signal measurements and to return the results of such router/distributor 23 and the output queue 21, and to initiate measurements to the signal processing system regarding the signal measurements within the wireless network, in mobile station to be located. This step may be accomplished response from an Internet 468 location request message in via several interface means. In a first case the controller 15 FIG. 5, via the location application programming interface. utilizes, for a given MSC, predetermined storage information In addition the controller 15 receives autonomous mes in the MSC table 31 to determine which type of commands, sages from the MSC, via the location applications program Such as man-machine or OSI commands are needed to request ming interface or L-API 14 (FIG. 30) and the input queue 7, such signal measurements for a given MSC. The controller whenevera 911 wireless call is originated. The mobile switch generates the mobile and base station signal measurement center provides this autonomous notification to the location commands appropriate for the MSC and passes the com system as follows; by specifying the appropriate mobile 25 mands via the input queue 7 and the locations application Switch center operations and maintenance commands to Sur programming interface 14 in FIG. 30, to the appropriate veil calls based on certain digits dialed such as 911, the MSC, using the authorized communications port mentioned location applications programming interface 14, in commu earlier. In a second case, the controller 15 communicates nications with the MSCs, receives an autonomous notifica directly with base stations within having to interface directly tion whenever a mobile station user dials 911. Specifically, a 30 with the MSC for signal measurement extraction. bi-directional authorized communications port is configured, Upon receipt of the signal measurements, the signal clas usually at the operations and maintenance subsystem of the sifier 9 in FIG. 30 examines location application program MSCs, or with their associated network element manager ming interface-provided message header information from system(s), with a data circuit, such as a DS-1, with the loca the source of the location measurement (for example, from a tion applications programming interface 14. Next, the "call 35 fixed BS 122, a mobile station 140, a distributed antenna trace’ capability of the mobile switch center is activated for system 168 in FIG. 4 or message location data related to a the respective communications port. The exact implementa home base station), provided by the location applications tion of the vendor-specific man-machine or Open Systems programming interface (L-API 14) via the input queue 7 in Interface (OSI) command(s) and their associated data struc FIG. 30 and determines whether or not device filters 17 or tures generally vary among MSC vendors. However, the trace 40 image filters 19 are needed, and assesses a relative priority in function is generally available in various forms, and is processing, Such as an emergency versus a background loca required in order to comply with Federal Bureau of Investi tion task, in terms of grouping like data associated with a gation authorities for wire tap purposes. After the appropriate given location request. In the case where multiple signal surveillance commands are established on the MSC, such911 measurement requests are outstanding for various base sta call notifications messages containing the mobile station 45 tions, some of which may be associated with a different identification number (MIN) and, in U.S. FCC phase 1 E911 CMRS network, and additional signal classifier function implementations, a pseudo-automatic number identification includes sorting and associating the appropriate incoming (a.k.a.p.ANI) which provides an association with the primary signal measurements together Such that the digital signal base station in which the 911 caller is in communication. In processor 17 processes related measurements in order to cases where the paNI is known from the onset, the signal 50 build ensemble data sets. Such ensembles allow for a variety processing subsystem 1220 avoids querying the MSC in of functions such as averaging, outlier removal over a time question to determine the primary base station identification period, and related filtering functions, and further prevent associated with the 911 mobile station caller. association errors from occurring in location estimate pro After the signal processing controller 15 receives the first cessing. message type, the autonomous notification message from the 55 Another function of the signal classifier/low pass filter mobile switch center 112 to the location system 142, contain component 9 is to filter information that is not useable, or ing the mobile identification number and optionally the pri information that could introduce noise or the effect of noise in mary base station identification, the controller 15 queries the the location estimate modules. Consequently low pass match base station table 13 (FIG. 30) in the signal processor data ing filters are used to match the in-common signal processing base 26 to determine the status and availability of any neigh 60 components to the characteristics of the incoming signals. boring base stations, including those base stations of other Low pass filters match: Mobile Station, base station, CMRS CMRS in the area. The definition of neighboring base stations and MSC characteristics, as well as to classify Home Base includes not only those within a provisionable “hop' based on Station messages. the cell design reuse factor, but also includes, in the case of The signal processing Subsystem 1220 contains a base CDMA, results from remaining set information autono 65 station database table 13 (FIG. 30) which captures the maxi mously queried to mobile stations, with results stored in the mum number of CDMA delay spread fingers for a given base base station table. Remaining set information indicates that station. US 9,134,398 B2 35 36 The base station identification code, or CLLI or common required across the air interface, in order to determine the language level identification code is useful in identifying or mobile station MIN characteristics. The resulting mobile sta relating a human-labeled name descriptor to the Base Station. tion information my be provided either via the signal process Latitude, Longitude and elevation values are used by other ing database 26 or alternatively a query may be performed Subsystems in the location system for calibration and estima 5 directly from the signal processing subsystem 1220 to the tion purposes. As base stations and/or receiver characteristics MSC in order to determine the mobile station characteristics. are added, deleted, or changed with respect to the network Referring now to FIG. 31, another location application used for location purposes, this database table must be modi programming interface, L-API-CCS 239 to the appropriate fied to reflect the current network configuration. CMRS customer care system provides the mechanism to Just as an upgraded base station may detect additional 10 populate and update the mobile station table 11 within the CDMA delay spread signals, newer or modified mobile sta database 26. The L-API-CCS 239 contains its own set of tions may detect additional pilot channels or CDMA delay separate input and output queues or similar implementations spread fingers. Additionally different makes and models of and security controls to ensure that provisioning data is not mobile stations may acquire improved receiver sensitivities, sent to the incorrect CMRS, and that a given CMRS cannot Suggesting a greater coverage capability. A table may estab 15 access any other CMRS data. The interface 1155a to the lish the relationships among various mobile station equip customer care system for CMRS-A 1150a provides an ment Suppliers and certain technical data relevant to this autonomous or periodic notification and response application location invention. layer protocol type, consisting of add, delete, change and Although not strictly necessary, the MIN can be populated Verify message functions in order to update the mobile station in this table from the PCS Service Provider's Customer Care table 11 within the signal processing database 26, via the system during Subscriber activation and fulfillment, and controller 15. A similar interface 155b is used to enable could be changed at deactivation, or anytime the end-user provisioning updates to be received from CMRS-B customer changes mobile stations. Alternatively, since the MIN, manu care system 1150b. facturer, model number, and software revision level informa Although the L-API-CCS application message set may be tion is available during a telephone call, this information 25 any protocol type which Supports the autonomous notifica could extracted during the call, and the remainingfields popu tion message with positive acknowledgment type, the lated dynamically, based on manufacturer's specifications T1M1.5 group within the American National Standards Insti information previously stored in the signal processing Sub tute has defined a good starting point in which the L-API-CCS system 1220. Default values are used in cases where the MIN 239 could be implemented, using the robust OSI TMN X-in is not found, or where certain information must be estimated. 30 terface at the service management layer. The object model A low pass mobile station filter, contained within the signal defined in Standards proposal number T1M1.5/96-22R9. classifier/low pass filter 9 of the signal processing subsystem Operations Administration, Maintenance, and Provisioning 1220, uses the above table data to perform the following (OAM&P) Model for Interface Across Jurisdictional functions: 1) act as a low pass filter to adjust the nominal Boundaries to Support Electronic Access Service Ordering: assumptions related to the maximum number of CDMA fin 35 Inquiry Function, can be extended to support the L-API-CCS gers, pilots detectable; and 2) to determine the transmit power information elements as required and further discussed class and the receiver thermal noise floor. Given the detected below. Other choices in which the L-API-CCS application reverse path signal strength, the required value of SRSSs a message set may be implemented include ASCII, binary, or corrected indication of the effective path loss in the reverse any encrypted message set encoding using the Internet pro direction (mobile station to BS), can be calculated based on 40 tocols, such as TCP/IP simple network management proto data contained within the mobile station table 11, stored in the col, http, https, and email protocols. signal processing database 26. Referring to the digital signal processor (DSP) 17, in com The effects of the maximum number of CDMA fingers munication with the signal classifier/LP filter 9, the DSP 17 allowed and the maximum number of pilot channels allowed provides a time series expansion method to convert non-HBS essentially form a low pass filter effect, wherein the least 45 data from a format of an signal measure data ensemble of common denominator of characteristics are used to filter the time-series based radio frequency data measurements, col incoming RF signal measurements such that a one for one lected as discrete time-slice samples, to a three dimensional matching occurs. The effect of the transmit power class and matrix location data value image representation. Other tech receiver thermal noise floor values is to normalize the char niques further filter the resultant image in order to furnish a acteristics of the incoming RF signals with respect to those 50 less noisy training and actual data sample to the location RF signals used. estimate modules. The signal classifier/filter 9 (FIG. 30) is in communication After 128 samples (in one embodiment) of data are col with both the input queue 7 and the signal processing database lected of the delay spread-relative signal strength RF data 26. In the early stage of a location request the signal process measurement sample, mobile station RX for BS-1 are ing subsystem 1220 shown in, e.g., FIGS. 5, 30 and 31, will 55 grouped into a quantization matrix, where rows constitute receive the initiating location request from either an autono relative signal strength intervals and columns define delay mous 911 notification message from a given MSC, or from a intervals. Each measurement row, column pair (which could location application, for which mobile station characteristics be represented as a complex number or Cartesian point pair) about the target mobile station 140 (FIG. 4) is required. Refer is added to their respective values to generate a Z direction of ring to FIG. 30, a query is made from the signal processing 60 frequency of recurring measurement value pairs or a density controller 15 to the signal processing database 26, specifically recurrence function. By next applying a grid function to each the mobile station table 11, to determine if the mobile station X, y, and Z value, a three-dimensional Surface grid is gener characteristics associated with the MIN to be located is avail ated, which represents a location data value or unique print of able in table 11. If the data exists then there is no need for the that 128-sample measurement. controller 15 to query the wireless network in order to deter 65 In the general case where a mobile station is located in an mine the mobile station characteristics, thus avoiding addi environment with varied clutter patterns, such as terrain tional real-time processing which would otherwise be undulations, unique man-made structure geometries (thus US 9,134,398 B2 37 38 creating varied multipath signal behaviors), such as a city or pass a 4x4 neighbor Median filter as well as a 40 to 50 percent suburb, although the first CDMA delay spread finger may be Input Crop filter, and are thus more Suited to neural net pattern the same value for a fixed distance between the mobile station recognition. However when Subjected to a 4x4 neighbor and BS antennas, as the mobile station moves across Such an Median filter and 40 percent clipping, pencil-shaped fingers area, different finger-data are measured. In the right image for are deleted. Other combinations include, for example, a 50 the defined BS antenna sector, location classes, or squares percent cropping and 4x4 neighbor median filtering. Other numbered one through seven, are shown across a particular filtering methods include custom linear filtering, adaptive range of line of position (LOP). (Weiner) filtering, and custom nonlinear filtering. A traditional TOA/TDOA ranging method between a given The DSP 17 may provide data ensemble results, such as BS and mobile station only provides a range along an arc, thus 10 extracting the shortest time delay with a detectable relative introducing ambiguity error. However a unique three dimen signal strength, to the router/distributor 23, or alternatively sional image can be used in this method to specifically iden results may be processed via one or more image filters 19, tify, with recurring probability, a particular unique location with subsequent transmission to the router/distributor 23. The class along the same Line Of Position, as long as the multi router/distributor 23 examines the processed message data path is unique by position but generally repeatable, thus 15 from the DSP 17 and stores routing and distribution informa establishing a method of not only ranging, but also of com tion in the message header. The router/distributor 23 then plete latitude, longitude location estimation in a Cartesian forwards the data messages to the output queue 21, for Sub space. In other words, the unique shape of the “mountain sequent queuing then transmission to the appropriate location image' enables a correspondence to a given unique location estimator FOMs. class along a line of position, thereby eliminating traditional Location Center High Level Functionality ambiguity error. At a very high level the location center 142 computes Although man-made external sources of interference, Ray location estimates for a wireless Mobile Station 140 (denoted leigh fades, adjacent and co-channel interference, and vari the “target MS’’ or “MS) by performing the following steps: able clutter, Such as moving traffic introduce unpredictability (23.1) receiving signal transmission characteristics of com (thus no “mountain image would ever be exactly alike), three 25 munications communicated between the target MS 140 and basic types offiltering methods can be used to reduce match one or more wireless infrastructure base stations 122; ing/comparison error from a training case to a location (23.2) filtering the received signal transmission characteris request case: (1) select only the strongest signals from the tics (by a signal processing subsystem 1220 illustrated in FIG. forward path (BS to mobile station) and reverse path (mobile 5) as needed so that target MS location data can be generated station to BS), (2) convolute the forward path 128 sample 30 that is uniform and consistent with location data generated image with the reverse path 128 sample image, and (3) pro from other target MSs 140. In particular, such uniformity and cess all image samples through various digital image filters to consistency is both in terms of data structures and interpreta discard noise components. tion of signal characteristic values provided by the MS loca In one embodiment, convolution of forward and reverse tion data; images is performed to drive out noise. This is one embodi 35 (23.3) inputting the generated target MS location data to one ment that essentially nulls noise completely, even if strong or more MS location estimating models (denoted First order and recurring, as long as that same noise characteristic does models or FOMs, and labeled collectively as 1224 in FIG. 5), not occur in the opposite path. so that each Such model may use the input target MS location The third embodiment or technique of processing CDMA data for generating a "location hypothesis' providing an esti delay spread profile images through various digital image 40 mate of the location of the target MS 140; filters, provides a resultant “image enhancement in the sense (23.4) providing the generated location hypotheses to an of providing a more stable pattern recognition paradigm to the hypothesis evaluation module (denoted the hypothesis evalu neural net location estimate model. For example, image his ator 1228 in FIG. 5): togram equalization can be used to rearrange the images (a) for adjusting at least one of the target MS location intensity values, or density recurrence values, so that the 45 estimates of the generated location hypotheses and related image's cumulative histogram is approximately linear. confidence values indicating the confidence given to each Other methods which can be used to compensate for a location estimate, wherein such adjusting uses archival infor concentrated histogram include: (1) Input Cropping, (2) Out mation related to the accuracy of previously generated loca put Cropping and (3) Gamma Correction. Equalization and tion hypotheses, input cropping can provide particularly striking benefits to a 50 (b) for evaluating the location hypotheses according to CDMA delay spread profile image. Input cropping removes a various heuristics related to, for example, the radio coverage large percentage of random signal characteristics that are area 120 terrain, the laws of physics, characteristics of likely non-recurring. movement of the target MS 140; and Other filters and/or filter combinations can be used to help (c) for determining a most likely location area for the target distinguish between stationary and variable clutter affecting 55 MS 140, wherein the measurement of confidence associated multipath signals. For example, it is desirable to reject mul with each input MS location area estimate is used for deter tipath fingers associated with variable clutter, since over a mining a “most likely location area'; and period of a few minutes Such fingers would not likely recur. (23.5) outputting a most likely target MS location estimate to Further filtering can be used to remove recurring (at least one or more applications 146 (FIG. 5) requesting an estimate during the sample period), and possibly strong but narrow 60 of the location of the target MS 140. “pencils’ of RF energy. A narrow pencil image component Location Hypothesis Data Representation could be represented by a near perfect reflective surface, such In order to describe how the steps (23.1) through (23.5) are as a nearby metal panel truck stopped at a traffic light. performed in the sections below, some introductory remarks On the other hand, stationary clutter objects, such as con related to the data denoted above as location hypotheses will crete and glass building Surfaces, adsorb some radiation 65 be helpful. Additionally, it will also be helpful to provide before continuing with a reflected ray at some delay. Such introductory remarks related to historical location data and stationary clutter-affected CDMA fingers are more likely to the database management programs associated therewith. US 9,134,398 B2 39 40 For each targetMS location estimate generated and utilized hood that the target MS 140 is in (or at) a corresponding MS by an embodiment of a wireless location system according to location estimate of the location hypothesis to which the the present disclosure, the location estimate is provided in a confidence value applies. As an aside, note that a location data structure (or object class) denoted as a "location hypoth hypothesis may have more than one MS location estimate (as esis” (illustrated in Table LH-1). Although brief descriptions will be discussed in detail below) and the confidence value of the data fields for a location hypothesis is provided in the will typically only correspond or apply to one of the MS Table LH-1, many fields require additional explanation. location estimates in the location hypothesis. Further, values Accordingly, location hypothesis data fields are further for the confidence value field may be interpreted as: (a) -1.0 described as noted below. may be interpreted to mean that the target MS 140 is NOT in TABLE LH-1 FOM ID First order model ID (providing this Location Hypothesis); note, since it is possible for location hypotheses to be generated by other than the FOMs 1224, in general, this field identifies the module that generated this location hypothesis. MS ID The identification of the target MS 140 to this location hypothesis applies. pt est The most likely location point estimate of the target MS 140. valid pt Boolean indicating the validity of “pt est'. area eSt Location Area Estimate of the target MS 140 provided by the FOM. This area estimate will be used whenever “image area below is NULL. valid area Boolean indicating the validity of “area est' (one of “pt est' and “area est' must be valid). adjust Boolean (true if adjustments to the fields of this location hypothesis are to be performed in the Context adjuster Module). pt covering Reference to a substantially minimal area (e.g., mesh cell) covering of pt est. Note, since this MS 140 may be substantially on a cell boundary, this covering may, in some cases, include more than one cell. image area Reference to a substantially minimal area (e.g., mesh cell) covering of pt covering (see detailed description of the function, "confidence adjuster). Note that if this field is not NULL, then this is the target MS location estimate used by the location center 142 instead of “area est'. extrapolation area Reference to (if non-NULL) an extrapolated MS target estimate area provided by the location extrapolator submodule 1432 of the hypothesis analyzer 1332. That is, this field, if non-NULL, is an extrapolation of the “image area field i it exists, otherwise this field is an extrapolation of the “area estfiel . Note other extrapolation fields may also be provided depending on the embodiment of the present disclosure, such as an extrapolation of the “pt covering. confidence A real value in the range -1.0, +1 .0 indicating a likelihood that the targetMS 40 is in (or out) of a particular area. If positive: if image area exists, then his is a measure of the likelihood hat the target MS 140 is within the area represented by image area, or i “image area has not been computed (e.g., “adjust is FALSE), hen “area est' must be valid and this is a measure of the ikelihood that he target MS 140 is within the area represented by “area est'. If negative, then area est' must be valid and this is a measure of the likelihood hat the target MS 140 is NOT in the area represented by “area est'. If it is zero near Zero), then the ikelihood is unknown. Original Timestamp Date and time hat the location signature cluster (defined hereinbelow) for this ocation hypothesis was received by the signal processing Subsystem 1220. Active Timestamp Run-time field providing the time o which this location hypothesis has had its MS location estimate(s) extrapolated (in the location extrapolator 1432 of the hypothesis analyzer 332). Note that this field is initialized with the value from he “Original Timestamp' field. Processing Tags and For indicating particular types of environmental classifications not readily environmental categorizations determined by he “Original Timestamp' field (e.g., weather, traffic), and restrictions on ocation hypothesis processing. loc sig cluster Provides access to the collection of location signature signal characteristics derived from communications between the target MS 140 and the base station(s) detected by this MS (discussed in detail hereinbelow); in particular, the location data accessed here is provided to the first order models by the signal processing Subsystem 1220; i.e., access to the “loc sigs (received at timestamp regarding the location of the targetMS) descriptor Original descriptor (from the First order model indicating why ?how the Location Area Estimate and Confidence Value were determined).

As can be seen in the Table LH-1, each location hypothesis Such a corresponding MS area estimate of the location data structure includes at least one measurement, denoted hypothesis area, (b) O may be interpreted to mean that it is hereinafter as a confidence value (or simply confidence), that unknown as to the likelihood of whether the MS 140 in the is a measurement of the perceived likelihood that an MS 60 corresponding MS area estimate, and (c) +1.0 may be inter location estimate in the location hypothesis is an accurate preted to mean that the MS 140 is perceived to positively be in location estimate of the target MS 140. Since such confidence the corresponding MS area estimate. values are an important aspect of the present disclosure, much Additionally, note that it is within the scope of the present of the description and use of Such confidence values are disclosure that the location hypothesis data structure may also described below; however, a brief description is provided 65 include other related “perception” measurements related to a here. Each such confidence value is in the range -1.0 to 1.0, likelihood of the target MS 140 being in a particular MS wherein the larger the value, the greater the perceived likeli location area estimate. For example, it is within the scope of US 9,134,398 B2 41 42 the present disclosure to also utilize measurements such as, (23.8.1) substantially invariant terrain characteristics (both (a) “sufficiency factors' for indicating the likelihood that an natural and man-made) of the area; e.g., mountains, MS location estimate of a location hypothesis is sufficient for buildings, lakes, highways, bridges, building density; locating the target MS 140; (b) “necessity factors' for indi (23.8.2) time varying environmental characteristics (both cating the necessity that the target MS be in an particular area natural and man-made) of the area; e.g., foliage, traffic, estimate. However, to more easily describe embodiments of weather, special events such as baseball games; wireless location systems and/or methods according to the (23.8.3) wireless communication components or infra present disclosure, a single confidence field is used having the structure in the area; e.g., the arrangement and signal interpretation given above. communication characteristics of the base stations 122 Additionally, in utilizing location hypotheses in, for 10 in the area. Further, the antenna characteristics at the example, the location evaluator 1228 as in (23.4) above, it is base stations 122 may be important criteria. important to keep in mind that each location hypothesis con Accordingly, a description of wireless signal characteris fidence value is a relative measurement. That is, for confi tics for determining area types could potentially include a dences, cf. and cf., ifcf.< cf., then for a location hypotheses 15 characterization of wireless signaling attributes as they relate H and H having cf. and cf., respectively, the target MS 140 to each of the above criteria. Thus, an area type might be: is expected to more likely reside in a target MS estimate of H hilly, treed, suburban, having no buildings above 50feet, with than a target MS estimate of H. Moreover, if an area, A, is base stations spaced apart by two miles. However, a catego Such that it is included in a plurality of location hypothesis rization of area types is desired that is both more closely tied target MS estimates, then a confidence score, CS, can be to the wireless signaling characteristics of the area, and is assigned to A, wherein the confidence score for Such an area capable of being computed Substantially automatically and is a function of the confidences (both positive and negative) repeatedly over time. Moreover, for a wireless location sys for all the location hypotheses whose (most pertinent) target tem, the primary wireless signaling characteristics for catego MS location estimates contain A. That is, in order to deter rizing areas into at least minimally similar area types are: mine a most likely target MS location area estimate for out 25 thermal noise and, more importantly, multipath characteris putting from the location center 142, a confidence score is tics (e.g., multipath fade and time delay). determined for areas within the location center service area. Focusing for the moment on the multipath characteristics, More particularly, if a function, “f, is a function of the it is believed that (23.8.1) and (23.8.3) immediately above confidence(s) of location hypotheses, and f is a monotonic are, in general, more important criteria for accurately locating 30 an MS 140 than (23.8.2). That is, regarding (23.8.1), multi function in its parameters and f(cf. cf. cf. ..., cf)=CS for path tends to increase as the density of nearby vertical area confidences cf. of location hypotheses H, i=1,2,..., N, with changes increases. For example, multipath is particularly A contained in the area estimate for H, then “f” is denoted a problematic where there is a high density of high rise build confidence score function. Accordingly, there are many ings and/or where there are closely spaced geographic undu embodiments for a confidence score function f that may be 35 lations. In both cases, the amount of change in Vertical area utilized in computing confidence scores for embodiments of per unit of area in a horizontal plane (for some horizontal wireless location systems and/or methods disclosed herein; reference plane) may be high. Regarding (23.8.3), the greater C.9. the density of base stations 122, the less problematic multi (a) f(cf. cf. . . . , cf)=X.cf.-CS, path may become in locating an MS 140. Moreover, the (b)f(cf. cf. . . . , cf.) X cf." CS, n=1, 3, 5, . . . ; 40 arrangement of the base stations 122 in the radio coverage (c) f(cf. cf. . . . , cf)=X(K, cf.) FCS, wherein K, i=1, area 120 in FIG. 4 may affect the amount and severity of 2, ... are positive system (tunable) constants (possibly depen multipath. dent on environmental characteristics such as topography, Accordingly, it would be desirable to have a method and time, date, traffic, weather, and/or the type of base station(s) system for Straightforwardly determining area type classifi 122 from which location signatures with the target MS 140 45 cations related to multipath, and in particular, multipath due are being generated, etc.). to (23.8.1) and (23.8.3). The present disclosure provides such For the present description of the invention, the function f a determination by utilizing a novel notion of area type, as defined in (c) immediately above is utilized. However, for hereinafter denoted “transmission area type' (or, “(transmis obtaining a general understanding of the present disclosure, sion) area type' when both a generic area type classification the simpler confidence score function of (a) may be more 50 scheme and the transmission area type discussed hereinafter useful. It is important to note, though, that it is within the are intended) for classifying “similar areas, wherein each scope of the present disclosure to use other functions for the transmission area type class or category is intended to confidence score function. describe an area having at least minimally similar wireless Coverage Area: Area Types and their Determination signal transmission characteristics. That is, the novel trans The notion of “area type' as related to wireless signal 55 mission area type scheme of the present disclosure is based transmission characteristics has been used in many investiga on: (a) the terrain area classifications; e.g., the terrain of an tions of radio signal transmission characteristics. Some inves area surrounding a target MS 140, (b) the configuration of tigators, when investigating such signal characteristics of base stations 122 in the radio coverage area 120, and (c) areas have used somewhat naive area classifications such as characterizations of the wireless signal transmission paths urban, suburban, rural, etc. However, it is desirable for the 60 between a target MS 140 location and the base stations 122. purposes of the present disclosure to have a more operational In one embodiment of a method and system for determin definition of area types that is more closely associated with ing Such (transmission) area type approximations, a partition wireless signal transmission behaviors. (denoted hereinafter as Po) is imposed upon the radio cover To describe embodiments of the an area type scheme used age area 120 for partitioning for radio coverage area into in the present disclosure, some introductory remarks are first 65 Subareas, wherein each Subarea is an estimate of an area provided. Note that the wireless signal transmission behavior having included MS 140 locations that are likely to have is at for an area depends on at least the following criteria: least a minimal amount of similarity in their wireless signal US 9,134,398 B2 43 44 ing characteristics. To obtain the partition Po of the radio for a Subarea A of this category, there is a common group coverage area 120, the following steps are performed: of 5 base stations 122 with two-way signal detection (23.8.4.1) Partition the radio coverage area 120 into sub expected with most locations (e.g., within a first or sec areas, wherein in each Subarea is: (a) connected, (b) ond deviation) within A, there are 2 base stations that are variations in the lengths of chords sectioning the Subarea expected to be detected by a target MS 140 in Abut these through the centroid of the Subarea are below a prede base stations can not detect the target MS, and there is termined threshold, (c) the subarea has an area below a one base station 122 that is expected to be able to detect predetermined value, and (d) for most locations (e.g., a target MS in A but not be detected. within a first or second standard deviation) within the (23.8.4.5) Determine an area type categorization scheme Subarea whose wireless signaling characteristics have 10 for the subareas of P. Note that the subareas of P. may been verified, it is likely (e.g., within a first or second be categorized according to their similarities. In one standard deviation) that an MS 140 at one of these loca- embodiment, such categories may be somewhat similar tions will detect (forward transmission path) and/or will to the naive area types mentioned above (e.g., dense be detected (reverse transmission path) by a same col- urban, urban, Suburban, rural, mountain, etc.). However, lection of base stations 122. For example, in a CDMA 15 it is also an aspect of the present disclosure that more context, a first such collection may be (for the forward precise categorizations may be used. Such as a category transmission path) the active set of base stations 122, or, for all areas having between 20,000 and 30,000 square the union of the active and candidate sets, or, the union of feet of vertical area change per 11,000 square feet of the active, candidate and/or remaining sets of base sta- horizontal area and also having a high traffic Volume tions 122 detected by “most MSs 140 in the subarea. 20 (such a category likely corresponding to a “moderately Additionally (or alternatively), a second Such collection dense urban area type). may be the base stations 122 that are expected to detect (23.8.4.6) Categorize subareas of Po with a categorization MSs 140 at locations within the subarea. Of course, the scheme denoted the “Po categorization,” wherein for union or intersection of the first and second collections is each Po subarea, A, of Po a “Po area type' is determined also within the scope of the present disclosure for parti- 25 for A according to the following Substep(s): tioning the radio coverage area 120 according to (d) (a) Categorize A by the two categories from (23.8.4.4) above. It is worth noting that it is believed that base and (23.8.5) with which it is identified. Thus, A is station 122 power levels will be substantially constant. categorized (in a corresponding Po area type) both However, even if this is not the case, one or more col- according to its terrain and the base station infrastruc lections for (d) above may be determined empirically 30 ture configuration in the radio coverage area 120. and/or by computationally simulating the power output (23.8.4.7) For each Po Subarea, A, of Po perform the fol of each base station 122 at a predetermined level. More- lowing step(s): over, it is also worth mentioning that this step is rela- (a) Determine a centroid, C(A), for A: tively straightforward to implement using the data stored (b) Determine an approximation to a wireless transmis in the location signature database 1320 (i.e., the verified 35 sion path between C(A) and each base station 122 of location signature clusters discussed in detail hereinbe- a predetermined group of base stations expected to be low). Denote the resulting partition here as P. in (one and/or two-way) signal communication with (23.8.4.2) Partition the radio coverage area 120 into sub- most target MS 140 locations in A. For example, one areas, wherein each Subarea appears to have Substan- Such approximation is a straight line between C(A) tially homogeneous terrain characteristics. Note, this 40 and each of the base stations 122 in the group. How may be performed periodically Substantially automati- ever, other such approximations are within the scope cally by Scanning radio coverage area images obtained of the present disclosure, such as, a generally trian from aerial or satellite imaging. For example, Earth- gular shaped area as the transmission path, wherein a Watch Inc. of Longmont, Colo. can provide geographic first vertex of this area is at the corresponding base with 3 meter resolution from satellite imaging data. 45 station for the transmission path, and the sides of the Denote the resulting partition here as P. generally triangular shaped defining the first vertex (23.8.4.3) Overlay both of the above partitions of the radio have a smallest angle between them that allows A to coverage area 120 to obtain new subareas that are inter- be completely between these sides. sections of the Subareas from each of the above parti- (c) For each base station 122, BS, in the group men tions. This new partition is Po (i.e., Po-P intersect P), 50 tioned in (b) above, create an empty list, BS-list, and and the subareas of it are denoted as “Po Subareas”. put on this list at least the Po area types for the “sig Now assuming Po has been obtained, the subareas of P are nificant Po Subareas crossed by the transmission path provided with a first classification or categorization as fol- between C(A) and BS. Note that “significant Po lows: Subareas may be defined as, for example, the Po Sub (23.8.4.4) Determine an area type categorization scheme 55 areas through which at least a minimal length of the for the subareas of P. For example, a subarea, A, of P, transmission path traverses. Alternatively, such 'sig may be categorized or labeled according to the number nificant Po Subareas may be defined as those Po sub of base stations 122 in each of the collections used in areas that additionally are known or expected to gen (23.8.4.1)(d) above for determining subareas of P. erate Substantial multipath. Thus, in one such categorization scheme, each category 60 (d) Assign as the transmission area type for A as the may correspond to a single number X (such as 3), collection of BS-lists. Thus, any other P subarea wherein for a Subarea, A, of this category, there is a having the same (or Substantially similar) collection group of X (e.g., three) base stations 122 that are of lists of P area types will be viewed as having expected to be detected by a most target MSs 140 in the approximately the same radio transmission character area A. Other embodiments are also possible. Such as a 65 istics. categorization scheme wherein each category may cor Note that other transmission signal characteristics may be respond to a triple: of numbers such as (5. 2, 1), wherein incorporated into the transmission area types. For example, US 9,134,398 B2 45 46 thermal noise characteristics may be included by providing a closure to utilize such historical MS signal location data for third radio coverage area 120 partition, P., in addition to the enhancing the correctness and/or confidence of certain loca partitions of P and P. generated in (23.8.4.1) and (23.8.4.2) tion hypotheses as will be described in detail in other sections respectively. Moreover, the time varying characteristics of below. (23.8.2) may be incorporated in the transmission area type 5 Data Representations for the Location Signature Data Base frame work by generating multiple versions of the transmis There are four fundamental entity types (or object classes sion area types such that the transmission area type for a given in an object oriented programming paradigm) utilized in the Subarea of Po may change depending on the combination of location signature database 1320. Briefly, these data entities time varying environmental characteristics to be considered are described in the items (24.1) through (24.4) that follow: in the transmission area types. For instance, to account for 10 seasonality, four versions of the partitions P and P. may be (24.1) (verified) location signatures: Each such (verified) generated, one for each of the seasons, and Subsequently location signature describes the wireless signal characteristic generate a (potentially) different partition Po for each season. measurements between a given base station (e.g., BS 122 or Further, the type and/or characteristics of base station 122 LBS 152) and an MS 140 at a (verified or known) location antennas may also be included in an embodiment of the 15 associated with the (verified) location signature. That is, a transmission area type. Verified location signature corresponds to a location whose Accordingly, in one embodiment of the present disclosure, coordinates Such as latitude-longitude coordinates are whenever the term “area type' is used hereinbelow, transmis known, while simply a location signature may have a known sion area types as described hereinabove are intended. or unknown location corresponding with it. Note that the term Location Information Data Bases and Data (verified) location signature is also denoted by the abbrevia Location Data Bases Introduction tion, “(verified) locsig hereinbelow: It is an aspect of the present disclosure that MS location (24.2) (verified) location signature clusters: Each Such (veri processing performed by the location center 142 should fied) location signature cluster includes a collection of (veri become increasingly better at locating a target MS 140 both fied) location signatures corresponding to all the location by (a) building an increasingly more detailed model of the 25 signatures between a target MS 140 at a (possibly verified) signal characteristics of locations in the wireless service area presumed Substantially stationary location and each BS (e.g., for the location center 142 (and/or its FOMs), and also (b) by 122 or 152) from which the target MS 140 can detect the BS’s providing capabilities for the location center processing to pilot channel regardless of the classification of the BS in the adapt to environmental changes. target MS (i.e., for CDMA, regardless of whether a BS is in One way these aspects of the present disclosure are realized 30 is by providing one or more database management systems the MS’s active, candidate or remaining base station sets, as and databases for: one skilled in the art will understand). Note that for simplicity (a) storing and associating wireless MS signal characteris here, it is presumed that each location signature cluster has a tics with known locations of MSs 140 used in providing the single fixed primary base station to which the target MS 140 signal characteristics. Such stored associations may not only 35 synchronizes or obtains its timing; provide an increasingly better model of the signal character (24.3) “composite location objects (or entities): Each such istics of the geography of the service area, but also provide an entity is a more general entity than the Verified location sig increasingly better model of more changeable signal charac nature cluster. An object of this type is a collection of (veri teristics affecting environmental factors such as weather, sea fied) location signatures that are associated with the same MS Sons, and/or traffic patterns; 40 140 at substantially the same location at the same time and (b) adaptively updating the signal characteristic data stored each Such loc sig is associated with a different base station. so that it reflects changes in the environment of the service However, there is no requirement that a locsig from each BS area such as, for example, a new high rise building or a new 122 for which the MS 140 can detect the BS’s pilot channel is highway. included in the “composite location object (or entity); and Referring again to FIG.5 of the collective representation of 45 (24.4) MS location estimation data that includes MS location these databases is the location information databases 1232. estimates output by one or more MS location estimating first Included among these databases is a database for providing order models 1224, such MS location estimate data is training and/or calibration data to one or more trainable/ described in detail hereinbelow. calibratable FOMs 1224, as well as an archival database for It is important to note that a loc Sigis, in one embodiment, archiving historical MS location information related to the 50 an instance of the data structure containing the signal char performance of the FOMs. These databases will be discussed acteristic measurements output by the signal filtering and as necessary hereinbelow. However, a further brief introduc tion to the archival database is provided here. Accordingly, normalizing Subsystem also denoted as the signal processing the term, “location signature database' is used hereinafter to subsystem 1220 describing the signals between: (i) a specific denote the archival database and/or database management 55 base station 122 (BS) and (ii) a mobile station 140 (MS), system depending on the context of the discussion. The loca wherein the BS’s location is known and the MS’s location is tion signature database (shown in, for example, FIG. 6 and assumed to be substantially constant (during a 2-5 second labeled 1320) is a repository for wireless signal characteristic interval in one embodiment of the novel wireless system data derived from wireless signal communications between and/or method disclosed herein), during communication with an MS 140 and one or more base stations 122, wherein the 60 the MS 140 for obtaining a single instance of loc sig data, corresponding location of the MS 140 is known and also although the MS location may or may not be known. Further, stored in the location signature database 1320. More particu for notational purposes, the BS 122 and the MS 140 for a loc larly, the location signature database 1320 associates each sig hereinafter will be denoted the “BS associated with the loc such known MS location with the wireless signal character sig', and the “MS associated with the loc sig' respectively. istic data derived from wireless signal communications 65 Moreover, the location of the MS 140 at the time the loc sig between the MS 140 and one or more base stations 122 at this data is obtained will be denoted the “location associated with MS location. Accordingly, it is an aspect of the present dis the loc sig” (this location possibly being unknown). US 9,134,398 B2 47 48 Loc Sig Description (this Line not in Spec) signal strength and time delay. That is, the accumulations In particular, for each (verified) locsig includes the follow over a brief time interval of signal characteristic measure 1ng: ments between the BS 122 and the MS 140 (associated with (25.1) MS type: the make and model of the target MS 140 the loc sig) may be classified according to the two signal associated with a location signature instantiation; note that 5 characteristic dimensions (e.g., signal strength and corre the type of MS 140 can also be derived from this entry; e.g., sponding time delay). That is, by Sampling the signal char whether MS 140 is a handset MS, car-set MS, oran MS for acteristics and classifying the samples according to a mesh location only. Note as an aside, for at least CDMA, the type of discrete cells orbins, wherein each cell corresponds to a of MS 140 provides information as to the number offingers different range of signal strengths and time delays a tally of that may be measured by the MS, as one skilled in the will 10 the number of samples falling in the range of each cell can appreciate. be maintained. Accordingly, for each cell, its correspond (25.2) BS id: an identification of the base station 122 (or, ing tally may be interpreted as height of the cell, so that location base station 152) communicating with the target when the heights of all cells are considered, an undulating MS; or mountainous Surface is provided. In particular, for a cell (25.3) MS loc: a representation of a geographic location 15 mesh of appropriate fineness, the “mountainous Surface'. (e.g., latitude-longitude) or area representing a verified/ is believed to, under most circumstances, provide a contour known MS location where signal characteristics between that is substantially unique to the location of the target MS the associated (location) base station and MS 140 were 140. Note that in one embodiment, the signal samples are received. That is, if the “verified flag attribute (discussed typically obtained throughout a predetermined signal Sam below) is TRUE, then this attribute includes an estimated pling time interval of 2-5 seconds as is discussed elsewhere location of the target MS. If verified flag is FALSE, then in this specification. In particular, the signal topography this attribute has a value indicating “location unknown. characteristics retained for a loc sig include certain topo Note "MS loc' may include the following two subfields: graphical characteristics of Such a generated mountainous an area within which the target MS is presumed to be, Surface. For example, each loc sig may include: for each and a point location (e.g., a latitude and longitude pair) 25 local maximum (of the loc Sig Surface) above a predeter where the target MS is presumed to be (in one embodi mined noise ceiling threshold, the (signal strength, time ment this is the centroid of the area); delay) coordinates of the cell of the local maximum and the (25.4) verified flag: a flag for determining whether the loc sig corresponding height of the local maximum. Additionally, has been verified; i.e., the value here is TRUE if a location certain gradients may also be included for characterizing of MS loc has been verified, FALSE otherwise. Note, if 30 the “steepness of the surface mountains. Moreover, note this field is TRUE (i.e., the locsig is verified), then the base that in some embodiments, a frequency may also be asso station identified by BS id is the current primary base ciated with each local maximum. Thus, the data retained station for the target MS; for each selected local maximum can include a quadruple (25.5) confidence: a value indicating how consistent this loc of signal strength, time delay, height and frequency. Fur sig is with otherloc sigs in the location signature database 35 ther note that the data types here may vary. However, for 1320; the value for this entry is in the range 0, 1 with 0 simplicity, in parts of the description of locsig processing corresponding to the lowest (i.e., no) confidence and 1 related to the signal characteristics here, it is assumed that corresponding to the highest confidence. That is, the con the signal characteristic topography data structure here is a fidence factor is used for determining how consistent the vector; locsig is with other “similar verified loc sigs in the loca 40 (25.8) quality obj: signal quality (or error) measurements, tion signature database 1320, wherein the greater the con e.g., Eb/No values, as one skilled in the art will understand; fidence value, the better the consistency with other loc sigs (25.9) noise ceiling: noise ceiling values used in the initial in the database. Note that similarity in this context may be filtering of noise from the signal topography characteristics operationalized by at least designating a geographic proX as provided by the signal processing Subsystem 1220; imity of a locsig in which to determine if it is similar to 45 (25.10) power level: power levels of the base station (e.g., other loc sigs in this designated geographic proximity and/ 122 or 152) and MS 140 for the signal measurements; or area type (e.g., transmission area type as elsewhere (25.11) timing error: an estimated (or maximum) timing herein). Thus, environmental characteristics may also be error between the present (associated) BS (e.g., an infra used in determining similarities such as: similar time of structure base station 122 or a location base station 152) occurrence (e.g., of day, and/or of month), similar weather 50 detecting the target MS 140 and the current primary BS 122 (e.g., Snowing, raining, etc.). Note, these latter character for the target MS 140. Note that if the BS 122 associated istics are different from the notion of geographic proximity with the locsig is the primary base station, then the value since proximity may be only a distance measurement about here will be zero; a location. Note also that a loc sig having a confidence (25.12) cluster ptr: a pointer to the location signature com factor value below a predetermined threshold may not be 55 posite entity to which this loc Sig belongs. used in evaluating MS location hypotheses generated by (25.13) repeatable: TRUE if the loc sig is “repeatable” (as the FOMS 1224. described hereinafter), FALSE otherwise. Note that each (25.6) timestamp: the time and date the loc sig was received verified locsig is designated as either “repeatable' or “ran by the associated base station of BS id: dom'. A locsig is repeatable if the (verified/known) loca (25.7) signal topography characteristics: In one embodiment, 60 tion associated with the locsig is such that signal charac the signal topography characteristics retained can be rep teristic measurements between the associated BS 122 and resented as characteristics of at least a two-dimensional this MS can be either replaced at periodic time intervals, or generated Surface. That is, Such a surface is generated by updated Substantially on demand by most recent signal the signal processing Subsystem 1220 from signal charac characteristic measurements between the associated base teristics accumulated over (a relatively short) time interval. 65 station and the associated MS 140 (or a comparable MS) at For example, in the two-dimensional Surface case, the the verified/known location. Repeatable loc sigs may be, dimensions for the generated Surface may be, for example, for example, provided by stationary or fixed location MSs US 9,134,398 B2 49 50 140 (e.g., fixed location transceivers) distributed within 8, 1999, note, both PCT/US97/15933 and U.S. Pat. No. certain areas of a geographical region serviced by the loca 6,236.365 are incorporated fully by reference herein) pro tion center 142 for providing MS location estimates. That vides (methods for locsig objects) for “normalizing each is, it is an aspect of the present disclosure that each Such loc sig so that variations in signal characteristics resulting stationary MS 140 can be contacted by the location center 5 from variations in (for example) MS signal processing and 142 (via the base stations of the wireless infrastructure) at generating characteristics of different types of MS's may Substantially any time for providing a new collection (i.e., be deduced In particular, since wireless network designers cluster) of wireless signal characteristics to be associated are typically designing networks for effective use of hand with the verified location for the transceiver. Alternatively, set MS’s 140 having a substantially common minimum set repeatable loc sigs may be obtained by, for example, 10 of performance characteristics, the normalization methods obtaining location signal measurements manually from provided here transform the locsig data so that it appears as workers who regularly traverse a predetermined route though the locsig was provided by a common hand set MS through some portion of the radio coverage area; i.e., postal 140. However, other methods may also be provided to workers. “normalize' aloc sig so that it may be compared with loc A loc Sigis random if the locsig is not repeatable. Random 15 sigs obtained from other types of MS’s as well. Note that loc sigs are obtained, for example, from Verifying a Such normalization techniques include, for example, inter previously unknown target MS location once the MS polating and extrapolating according to power levels so 140 has been located. Such verifications may be accom that loc sigs may be normalized to the same power level for, plished by, for example, a vehicle having one or more e.g., comparison purposes. location verifying devices such as a GPS receiver and/or Normalization for the BS 122 associated with a locsig is a manual location input capability becoming sufficiently similar to the normalization for MS signal processing close to the located target MS 140 so that the location of and generating characteristics. Just as with the MS nor the vehicle may be associated with the wireless signal malization, the signal processing Subsystem 1220 pro characteristics of the MS 140. Vehicles having such vides alocsig method for “normalizing loc sigs accord location detection devices may include: (a) Vehicles that 25 ing to base station signal processing and generating travel to locations that are primarily for another purpose characteristics. than to Verify loc sigs, e.g., police cars, ambulances, fire Note, however, loc sigs stored in the location signature data trucks, rescue units, courier services and taxis; and/or base 1320 are NOT “normalized according to either (b) Vehicles whose primary purpose is to Verify loc sigs; MS or BS signal processing and generating characteris e.g., location signal calibration vehicles. Additionally, 30 tics. That is, "raw values of the wireless signal charac vehicles having both wireless transceivers and location teristics are stored with each loc sig in the location verifying devices may provide the location center 142 signature database 1320. with random loc sigs. Note, a repeatable loc sig may (26.2) A method for determining the “area type' correspond become a random loc sig if an MS 140 at the location ing to the signal transmission characteristics of the area(s) associated with the loc Sig becomes undetectable Such 35 between the associated BS 122 and the associated MS 140 as, for example, when the MS 140 is removed from its location for the loc sig. Note, such an area type may be verified location and therefore the locsig for the location designated by, for example, the techniques for determining can not be readily updated. transmission area types as described hereinabove. Additionally, note that at least in one embodiment of the (26.3.) Other methods are contemplated for determining addi signal topography characteristics (25.7) above. Such a first 40 tional environmental characteristics of the geographical Surface may be generated for the (forward) signals from the area between the associated BS 122 and the associated MS base station 122 to the target MS 140 and a second such 140 location for the loc sig; e.g., a noise value indicating surface may be generated for (or alternatively, the first surface the amount of noise likely in Such an area. may be enhanced by increasing its dimensionality with) the Referring now to the composite location objects and veri signals from the MS 140 to the base station 122 (denoted the 45 fied location signature clusters of (24.3) and (24.2) respec reverse signals). tively, the following information is contained in these aggre Additionally, in Some embodiments the location hypoth gation objects: esis may include an estimated error as a measurement of (27.1.1) an identification of the BS 122 designated as the perceived accuracy in addition to or as a Substitute for the primary base station for communicating with the targetMS confidence field discussed hereinabove. Moreover, location 50 140; hypotheses may also include a text field for providing a rea (27.1.2) a reference to each loc sig in the location signature son for the values of one or more of the location hypothesis database 1320 that is for the same MS location at substan fields. For example, this text field may provide a reason as to tially the same time with the primary BS as identified in why the confidence value is low, or provide an indication that (27.1); the wireless signal measurements used had a low signal to 55 (27.1.3) an identification of each base station (e.g., 122 and noise ratio. 152) that can be detected by the MS 140 at the time the Loc sigs have the following functions or object methods location signal measurements are obtained. Note that in associated therewith: one embodiment, each composite location object includes (26.1) A “normalization' method for normalizing locsig data a bit string having a corresponding bit for each base station, according to the associated MS 140 and/or BS 122 signal 60 wherein a “1” for such a bit indicates that the correspond processing and generating characteristics. That is, the sig ing base station was identified by the MS, and a “0” indi nal processing Subsystem 1220, one embodiment being cates that the base station was not identified. In an alterna described in the PCT patent application PCT/US97/15933, tive embodiment, additional location signal measurements titled, “Wireless Location Using A Plurality of Commer may also be included from other non-primary base stations. cial Network Infrastructures.” by F. W. LeBlanc and the 65 For example, the target MS 140 may communicate with present inventors, filed Sep. 8, 1997 (which has a U.S. other base stations than its primary base station. However, national filing that is now U.S. Pat. No. 6,236.365, filed Jul. since the timing for the MS 140 is typically derived from