Multiple-target tracking with radar applications

Preface	p. xii
Chapter 1 The Basics of Multiple-Target Tracking	p. 1
1.1 Introduction	p. 1
1.2 Basic Processing Definitions	p. 3
1.3 Elements of a Basic MTT System	p. 4
1.4 Overview of Data Association Issues	p. 11
1.5 Suggested Further Background Reading	p. 16
References	p. 16
Chapter 2 Methods for Filtering and Prediction	p. 19
2.1 Introduction	p. 19
2.2 Fixed-Coefficient Filtering	p. 21
2.3 Kalman Filtering	p. 25
2.4 Approximations and Simplifications of Kalman Filtering	p. 34
2.5 Maneuver Detection and Adaptive Filtering	p. 37
2.6 Summary and Conclusions	p. 43
References	p. 44
Appendix 2A Relationship between Equivalent Noise Bandwidth and Acceleration Error Constant	p. 46
Chapter 3 Choice of Tracking Coordinate System and Filtering State Variables	p. 49
3.1 Introduction	p. 49
3.2 Solution of the Continuous Linear State Equation	p. 51
3.3 North-East-Down (NED) Coordinate System	p. 52
3.4 Tracking in Cartesian Coordinates	p. 55
3.5 Polar Coordinate Systems	p. 56
3.6 A Comparative Study of Angle Filtering Methods	p. 65
3.7 Tracking with Angle-Only Measurements	p. 72
3.8 Summary	p. 72
References	p. 73
Appendix 3A Tracking Filter Development	p. 75
Appendix 3B Use of Range Rate for NED Velocity Component Estimation	p. 80
Chapter 4 Gating and Data Association	p. 83
4.1 Introduction	p. 83
4.2 Gating Techniques	p. 84
4.3 The Assignment Problem	p. 92
4.4 Simple Branching or Track Splitting	p. 98
4.5 Methods for State Estimation and Covariance Modification to Account for Miscorrelation	p. 101
4.6 Summary	p. 105
References	p. 106
Appendix 4A Summary of Correlation Statistics	p. 108
Chapter 5 Measurement Formation and Processing for Multiple-Target Tracking	p. 115
5.1 Introduction	p. 115
5.2 Overview of Feedback between Tracking and Detection Functions	p. 116
5.3 Adaptive Thresholding for Enhanced Detection and Tracking Performance	p. 117
5.4 Measurement Processing for a Clutter Background	p. 124
5.5 Observation Redundancy Elimination	p. 126
5.6 Methods for Determining Target Multiplicity (Range/Range Rate Resolution)	p. 129
5.7 Target Multiplicity Detection through Monopulse Angle Processing	p. 130
5.8 Measurement Degradation due to Jet Engine Modulation and Electronic Countermeasures	p. 138
5.9 Summary	p. 141
References	p. 142
Appendix 5A Derivation of Optimal Threshold Setting	p. 143
Appendix 5B Derivations for Target Multiplicity Detection Method	p. 146
Chapter 6 Definitions of Track Life Stages (Track Initiation, Confirmation, Deletion, and Quality)	p. 151
6.1 Introduction	p. 151
6.2 Track Confirmation Using Sequential Analysis	p. 152
6.3 Bayesian Track Confirmation	p. 156
6.4 Batch Processing Techniques for Track Initiation and Confirmation	p. 159
6.5 Indicators of Track Quality (Score)	p. 168
6.6 Track Deletion	p. 171
6.7 Summary	p. 173
References	p. 174
Appendix 6A Approximate Distribution for a Weighted Sum of Chi-Square Variables	p. 176
Appendix 6B Score Associated with Clutter Point Designation	p. 177
Chapter 7 Analytic Techniques For System Evaluation	p. 179
7.1 Introduction	p. 179
7.2 Covariance Analysis	p. 179
7.3 Techniques for Estimating Correlation Performance	p. 186
7.4 Track Confirmation and Retention Statistics Using Markov Chain Techniques	p. 193
7.5 Extensions of Markov Chain Techniques	p. 204
7.6 Summary	p. 210
References	p. 211
Chapter 8 Design Of A Detailed Multiple-Target Tracking Simulation	p. 213
8.1 Introduction	p. 213
8.2 Generation and Use of Random Numbers	p. 213
8.3 Modeling the Radar Detection Process	p. 217
8.4 Monte Carlo Simulation Design and Interpretation of Results	p. 223
8.5 Selection of Evaluation Statistics	p. 228
8.6 Simulation Development	p. 234
References	p. 244
Appendix 8A A General Technique for Generating Random Numbers	p. 245
Appendix 8B Derivation of the Correlation Properties of an Exponentially Distributed Random Variable	p. 246
Chapter 9 A Maximum Likelihood Expression For Data Association	p. 249
9.1 Introduction	p. 249
9.2 Generalized Technique Development	p. 250
9.3 Applications	p. 260
9.4 Development of a Sequential Correlation Technique	p. 264
9.5 Extension to Multiple Observation-to-Track Correlations	p. 274
9.6 Summary	p. 279
References	p. 280
Chapter 10 The Bayesian Probabilistic Approach	p. 281
10.1 Introduction	p. 281
10.2 Multiple Hypothesis Tracking	p. 283
10.3 The All-Neighbors Data Association Approach (PDA, JPDA)	p. 299
10.4 Concluding Remarks	p. 305
References	p. 306
Chapter 11 Group Tracking	p. 309
11.1 Introduction	p. 309
11.2 Centroid Group Tracking	p. 312
11.3 Formation Group Tracking	p. 317
11.4 Summary and Extensions	p. 324
References	p. 325
Appendix 11A Processing for the Centroid Group Tracking Method	p. 325
Chapter 12 Applications Of The Radar Electronically Scanned Antenna To Multiple-Target Tracking	p. 329
12.1 Introduction	p. 329
12.2 Enhancing Radar Detection with the ESA	p. 331
12.3 Adaptive Sampling with the ESA	p. 333
12.4 ESA Techniques for Improving Nearest-Neighbor Correlation Performance	p. 342
12.5 Implementation of Multiple-Target Tracking Logic for an ESA System	p. 351
12.6 Summary	p. 355
References	p. 356
Chapter 13 The Use Of Multiple Sensors For Multiple-Target Tracking	p. 357
13.1 Introduction	p. 357
13.2 Sensor-Level and Central-Level Multiple Sensor Fusion	p. 359
13.3 Implementation of Sensor-Level Tracking	p. 363
13.4 Fusion and Correlation for Data Including Attributes	p. 368
13.5 The Dempster-Shafer (Evidential Reasoning) Method	p. 380
13.6 Sensor Allocation	p. 387
13.7 Summary	p. 392
References	p. 393
Appendix 13A Track Fusion Relationships	p. 395
Chapter 14 Special Topics	p. 397
14.1 Introduction	p. 397
14.2 A Solution for the Optimal Assignment Problem	p. 397
14.3 An Implementation Method for Multiple Hypothesis Tracking	p. 402
14.4 MTT Implementation in Dense Target Environments	p. 421
14.5 A Total System Architecture Including Multiple-Target Tracking	p. 429
References	p. 432
Glossary	p. 433
Index	p. 441

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