Location-Based Sensor Fusion for UAS Urban Navigation by Justin R. Rufa A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Aerospace Engineering) in the University of Michigan 2014 Doctoral Committee: Associate Professor Ella M. Atkins, Chair Professor Dennis S. Bernstein Associate Professor Ryan M. Eustice Assistant Professor James R. Forbes By Jeffmock (Own work) [GFDL (http://www.gnu.org/copyleft/fdl.html), CC-BY-SA-3.0 (http://creativecommons.org/licenses/by-sa/3.0/) or CC-BY-SA-2.5-2.0-1.0 (http://creativecommons.org/licenses/by-sa/2.5-2.0-1.0)], via Wikimedia Commons The only thing necessary for the triumph of evil is for good men to do nothing. Based on multiple quotes, most notably, Edmund Burke (1770) and John Stuart Mill (1867) ©Justin R. Rufa 2014 To my amazing wife Natalie, your patience is eternal, to my mother Glory, who taught me to never stop learning, and to my son Drew, who brought warmth to a long cold Michigan winter ii ACKNOWLEDGMENTS I would like to thank the United States Air Force Academy Department of Mathematical Sciences and their department head Colonel John Andrew for the opportunity to take three years of my career to earn a doctorate. It was the privilege of returning to their department to teach our nation’s future leaders that served as a constant reminder of why I undertook this endeavor. Their faith in me, their timely advice, and words of reassurance have gotten me through many tough times during this program. I am also grateful to the University of Michigan Department of Aerospace Engineering Graduate Committee for making the commitment to fund my tuition over the three year course of study in a somewhat unique circumstance. I would also like to thank my advisor Associate Professor Ella Atkins for her guidance, support, and wisdom as these constants kept me along the three year graduation path. The passion she shows for eliminating the nonsensical roadblocks to the safe use of small unmanned aircraft is an example to be followed by all in our respective fields of interest. I would finally like to thank my three additional dissertation committee members for their support and time in helping me produce a quality document to hopefully be used by students in the future. This includes Professor Associate Ryan Eustice, who spent at least a few hours teaching me the finer points of stochastic cloning, Professor Dennis Bernstein, and Assistant Professor James Forbes. Last, but not least, a huge thanks to Doctor Justin Bradley for giving my dissertation one final review before submittal. The views expressed in this dissertation are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the U.S. Government. iii TABLE OF CONTENTS Dedication ....................................... ii Acknowledgments ................................... iii List of Figures ..................................... vii List of Tables ...................................... x List of Appendices ................................... xii List of Acronyms .................................... xiii Abstract ......................................... xv Chapter 1 Introduction ..................................... 1 1.1 Expanding Urban-Focused UAS Missions.................1 1.2 GPS Degradation, Loss, or Denial in Urban Canyons...........2 1.3 Existing Urban Canyon Navigation Techniques..............5 1.3.1 GPS-Only Navigation.......................5 1.3.2 Navigation by GPS with Inertial Sensors.............7 1.3.3 Navigation by GPS with other Sensors...............8 1.3.4 Navigation by GPS with Inertial Sensors and Beacons......9 1.3.5 Navigation by GPS with Map Matching..............9 1.3.6 Navigation by GPS with Map Matching and Inertial Sensors... 10 1.3.7 Navigation by Environment-Based Sensors: Computer Vision and Laser.............................. 12 1.4 Problem Statement............................. 14 1.5 Research Objectives............................. 15 1.5.1 Approach.............................. 15 1.6 Contributions................................ 16 1.7 Innovations................................. 17 1.8 Dissertation Overview............................ 18 2 Background ..................................... 19 2.1 UAS Control using a Linear Quadratic Regulator (LQR)......... 19 iv 2.2 Fixed-Wing Rigid-Body Aircraft Equations of Motion........... 20 2.2.1 Rewriting UAS Equations of Motion in Terms of System States. 22 2.3 Aircraft Equation of Motion Linearization and Trim State Calculation.. 23 2.3.1 Linearization about a Trim Condition............... 24 2.3.2 Calculating a Trim Condition................... 26 2.4 UAS Sensors................................ 26 2.4.1 Inertial Measurement Unit (IMU)................. 27 2.4.2 Air Data System (ADS)...................... 28 2.4.3 Computer Vision-Based Sensors.................. 28 2.4.4 GPS Receiver............................ 32 2.4.5 LTE................................. 34 2.4.6 LiDAR............................... 40 2.5 Bayesian State Estimation Filters..................... 40 2.5.1 Kalman Filter Derivation...................... 41 2.5.2 Extended Kalman Filter...................... 46 2.5.3 Ensemble Kalman Filter...................... 47 2.5.4 Multi-Sensor Fusion Techniques.................. 50 2.5.5 Delayed Measurement Compensation............... 51 2.5.6 Filter Consistency and Accuracy Metrics............. 52 3 Development of the UAS GNC Simulation .................... 56 3.1 Simulation Flow............................... 57 3.2 Simulation Code Outline.......................... 57 3.2.1 Simulation Data Class....................... 59 3.2.2 Urban Environment Data Class.................. 60 3.2.3 UAS Dynamics Data Class..................... 63 3.2.4 Sensor Data Class......................... 64 3.2.5 Estimator Data Class........................ 66 3.3 Urban Environment Development..................... 67 3.4 UAS Model................................. 69 3.5 Linearization of the UAS Equations of Motion at Nominal Flight Conditions 71 3.5.1 Calculating Trim Conditions.................... 71 3.5.2 Linearizing about the Trim Conditions............... 72 3.5.3 Verifying the Linear Model.................... 74 3.6 Linear Quadratic Regulator Design.................... 77 3.7 Chapter Summary.............................. 78 4 Sensor Models and Filter Parameters for UAS Navigation in Urban Environ- ments ......................................... 79 4.1 Urban Environment Relative Location Categorization........... 79 4.1.1 Categorizing Street-Level Position................. 80 4.1.2 Categorizing Altitude with respect to Buildings.......... 81 4.2 UAS Urban Environment Sensors..................... 83 4.3 Sensor Measurement and Error Covariance Generation.......... 85 4.3.1 Sensor Availability......................... 88 v 4.3.2 Sensor Measurement Generation.................. 92 4.3.3 Sensor Error Covariance Determination for Available Sensors.. 92 4.4 Accounting for Delayed Measurements using State Augmentation.... 97 4.5 Particle Filter Ensemble Sizing....................... 97 4.6 Chapter Summary.............................. 100 5 Accuracy of Navigation in a Homogeneous Urban Environment ........ 102 5.1 Simulation Setup.............................. 102 5.1.1 Homogeneous Urban Environment................ 102 5.1.2 Test Matrix............................. 103 5.1.3 Simulation Parameters....................... 104 5.1.4 State Estimation Filters....................... 106 5.2 Results.................................... 107 5.2.1 Open Space Environment..................... 107 5.2.2 Canyons.............................. 110 5.2.3 Altitude, Airspeed, and Attitude Performance........... 114 5.3 Chapter Summary.............................. 116 6 Accuracy of Navigation in a Heterogeneous Urban Environment ........ 118 6.1 Simulation Description........................... 120 6.1.1 Heterogeneous Urban Environment................ 120 6.1.2 Sensors and Sensor Noise Covariance............... 120 6.1.3 Test Matrix............................. 123 6.2 Matched Model Results........................... 126 6.2.1 GPS Availability.......................... 126 6.2.2 Sensor Accuracy Mode....................... 131 6.2.3 Sinusoidal Flight Path through Environment............ 132 6.3 Unmatched Model Results......................... 136 6.3.1 Unmatched UAS Models...................... 140 6.3.2 Untuned Unmatched Model Results................ 142 6.3.3 Tuned Unmatched Model Results................. 145 6.3.4 Filter Accuracy Results....................... 152 6.4 Chapter Summary.............................. 158 7 Conclusions and Future Research Topics ..................... 160 7.1 Conclusions................................. 161 7.2 Future Research Topics........................... 163 Appendices ....................................... 167 Bibliography ...................................... 204 vi LIST OF FIGURES 1.1 Wanchai District of Hong Kong from Victoria Harbour courtesy of WiNG...3 1.2 Vancouver urban street-level image courtesy of MacGougan etal: .......6 1.3 Gorlitz¨ urban build-up images courtesy of Modsching etal: ...........7 2.1 Example of parallel lines and vanishing points using an urban scene courtesy of Hwangbo and Kanade.............................. 30 2.2 Smart phone geolocation techniques courtesy of Ericsson............ 35 2.3 OTDOA geolocation technique.......................... 37 3.1 UAS GNC simulation system diagram...................... 56 3.2 Simulation