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Bachelor Degree Project Multilateration in Direct Short Range Communications Networks

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Bachelor Degree Project Multilateration in Direct Short Range Communications Networks Bachelor Degree Project Multilateration in Direct Short Range Communications Networks - utilising Basic Safety Messages and Received Signal Strength ranging Author: Andrew Galbraith Supervisor: Francis Palma Semester: Spring 2020 Subject: Computer Science Abstract Traditional satellite positioning systems have limited resolution and have proved in- accurate in areas such as urban canyons where signals are subject to bounce phe- nomena or indeed may be entirely unavailable. An alternative method of positioning is that of tri/multilateration, which uses known positions and distances from beacon points to locate a receiver. In this project, a software was developed which used DSRC Basic Safety Messages (containing locational information) in combination with Received Signal Strength metrics (translated to distance information) to carry out such positioning in static environments. Initial studies confirmed that a signal received on the Craton 2 hardware was sub- ject to considerable signal strength spread approximating a Gaussian distribution. A software was developed to simulate BSMs, including a measure of perturbation, over TCP. Three different traffic scenarios were constructed. Furthermore, multilateration software was developed to receive the BSMs and calculate position using three sep- arate algorithms. The performance of these algorithms in the three different traffic scenarios was then evaluated. Lastly, the multilateration software was further de- veloped to allow for the capture and processing of real BSMs sent on the 5.9 GHz band. The multilateration software was capable of determining the location of the re- ceiver to varying degrees of accuracy, depending on the geometrical distribution of surrounding vehicles and the algorithm used to multilaterate. The 3D Linear Least Squares method performed well in situations where beacons were well spaced in three dimensions. Other implemented multilateration algorithms, i.e., a 2D Linear Least Squares method and a 3D Gauss Newton method, performed better in typical traffic scenarios where vehicles tend to be coplanar. The software developed provides a useful starting point for further development of static, but also dynamic, multilateration algorithms. Keywords: DSRC, trilateration, multilateration, RSS, V2X Preface I’m grateful to Cybercom Jönköping for the original concept, equipment loan and sup- port throughout the writing of this project. Particular thanks to Anna Blid and Bernard Mörtsell for taking the time to explain underlying concepts and for providing technical documentation (and general wisdom). Contents List of Figures1 List of Tables1 1 Introduction3 1.1 Background.................................3 1.1.1 DSRC and LTE-V2X........................3 1.1.2 Basic Safety Message (BSM)...................4 1.1.3 Multilateration...........................4 1.1.4 Hardware used...........................5 1.2 Related work................................5 1.3 Problem formulation............................6 1.4 Motivation..................................6 1.5 Objectives..................................6 1.6 Scope/Limitation..............................7 1.7 Target group.................................7 1.8 Outline...................................7 2 Method8 2.1 Overview..................................8 2.1.1 Languages and Libraries Used...................8 2.1.2 Build Environment and Initial Development............8 2.1.3 Data Collection...........................9 2.2 Reliability and Validity...........................9 2.3 Ethical considerations............................9 3 Implementation 10 3.1 Propagation Models............................. 10 3.1.1 Free Space Propagation Model................... 10 3.1.2 Empirical Free Space Model.................... 11 3.1.3 Two-ray Interference Model.................... 11 3.1.4 Model Comparison......................... 11 3.2 Coordinate Systems............................. 12 3.3 Multilateration Calculations........................ 13 3.3.1 Closed Form Multilateration with Linear Least Squares...... 13 3.3.2 Gauss-Newton Multilateration................... 14 3.3.3 Dilution of Precision........................ 14 3.4 Dataset Implementation........................... 16 3.5 Implementation of Beacon Simulator - BSM-beacon-sim......... 16 3.6 Implementation of Multilaterator - BSM-multilaterator.......... 17 3.6.1 Usage................................ 18 3.6.2 Dependencies and attributions.................... 19 3.6.3 Notes concerning Program Structure................ 19 3.6.4 Known Bugs............................ 20 3.7 Generated Datasets............................. 21 3.7.1 New Mexico............................ 21 3.7.2 Chapultepec............................. 21 3.7.3 E4.................................. 21 4 Results 24 4.1 Received Signal Strength Spread, Indoor Environment.......... 24 4.2 Received Signal Strength, Indoor Environment.............. 24 4.3 Multilaterator Simulated Performance................... 25 4.3.1 New Mexico Dataset........................ 25 4.3.2 Chapultepec Dataset........................ 25 4.3.3 E4 Dataset............................. 25 4.3.4 Mean Error of Multilateration Algorithms............. 25 4.3.5 Average Calculation Times of Multilateration Algorithms.... 26 5 Analysis 28 5.1 Received Signal Strength Spread, Indoor Environment.......... 28 5.2 Received Signal Strength, Indoor Environment.............. 28 5.3 Multilaterator Simulated Performance................... 28 5.4 Average Calculation Times of Multilateration Algorithms......... 28 6 Discussion 29 6.1 RSS to Distance............................... 29 6.2 Multilateration............................... 29 6.3 Methodology Shortcomings......................... 30 7 Conclusion 31 7.1 Future work................................. 31 References 32 A Appendix 1A B Appendix 2A List of Figures 1.1 The WAVE Stack..............................4 1.2 Progression of trilateration.........................5 3.3 Path Loss Model Comparison (Ptx = 33dBm, γ =2.5, =5)........ 12 3.4 Earth Centered, Earth Fixed Coordinate System.............. 13 3.5 East North Up (ENU) Coordinate System................. 13 3.6 Geometric Dilution of Precision (GDOP)................. 15 3.7 Overview of trilateration system...................... 17 3.8 Multilaterator NCurses GUI........................ 19 3.9 Chapultepec Dataset (distances in m).................... 22 3.10 E4 Dataset (distances in m)......................... 22 4.11 Typical signal spread for recorded signal strength (Ptx = 4dBm, d = 30m, n=397, indoor environment)........................ 24 4.12 Reported average RSS (n=566) between two Craton 2 EVKs in an indoor environment (Ptx = 4dBm, α = 2, = 5, h = 0:5,n = 566, indoor environment)... 24 4.13 Performance of Multilateration Algorithms for New Mexico Dataset.... 25 4.14 Performance of Multilateration Algorithms for Chapultepec Dataset (LLS 3D Algorithm Excluded)........................... 26 4.15 Performance of Multilateration Algorithms for E4 Dataset (LLS 3D Al- gorithm Excluded).............................. 26 List of Tables 3.1 Path Loss Exponents for Various Environments [1]............ 11 3.2 Dilution of Precision for New Mexico Dataset............... 21 3.3 Dilution of Precision for Chapultepec Dataset............... 21 3.4 Dilution of Precision for E4 Dataset.................... 23 4.5 Mean Error of Multilateration Algorithms/m (n=20)............ 26 4.6 Mean Calculation Time of Multilateration Algorithms in seconds (n=20). Number of beacons shown in parentheses.................. 27 1.7 BSM Contents................................A Acronyms BSM Basic Safety Message. DSRC Dedicated Short Range Communications. ECEF Earth-Centered Earth-Fixed coordinate system. ENU East North Up coordinate system. EVK Evaluation Kit. GNSS Global Navigation Satellite System. GSL GNU Scientific Library. ITS Intelligent Transport System. NED North East Down coordinate system. RSS Received Signal Strength. TDOA Time Difference of Arrival. TOA Time of Arrival. V2X Vehicle To Everything. WAVE Wireless Access in Vehicular Environments. 2 1 Introduction 1.1 Background The advent of intelligent transport systems (Intelligent Transport System (ITS)s) brings with it the challenge of communication between vehicles and other relevant entities, e.g., infrastructure or surrounding vehicles and pedestrians. Such communication has the po- tential to not only maximise road safety but also to improve factors such as traffic flow and vehicular energy consumption. Standards such as Vehicle To Everything (V2X) (Ve- hicle to Everything) have been developed to facilitate this information exchange. Central to V2X and other such standards is a vehicle’s ability to determine its position accurately. Traditional Global Navigation Satellite System (Global Navigation Satellite System (GNSS)) positioning systems have limited resolution and additionally have proved inac- curate in areas such as urban canyons where the necessary GNSS signals may be subject to bounce phenomena or indeed may be entirely unavailable [2]. Various solutions have therefore been suggested to augment GNSS information; several of these concern pro- cessing signal data broadcast from surrounding vehicles or infrastructural elements. For example, both Time of Arrival (Time of Arrival (TOA)) and Time Difference of Arrival Time Difference of Arrival (TDOA)) methods use the travel time of radio signals to de- termine distance from the transmitter to the receiver. Alternatively, and of relevance in this project, received signal strength
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