About the Authors xiv
Preface xvi
1 Introduction 1
1.1 Aim and Significance of Radar Data Processing 1
1.2 Basic Concepts in Radar Data Processing 2
1.2.1 Measurements 2
1.2.2 Measurement Preprocessing 2
1.2.3 Data Association 4
1.2.4 Wave Gate 4
1.2.5 Track Initiation and Termination 5
1.2.6 Tracking 5
1.2.7 Track 7
1.3 Design Requirements and Main Technical Indexes of Radar Data Processors 9
1.3.1 Basic Tasks of Data Processors 9
1.3.2 The Engineering Design of Data Processors 9
1.3.3 The Main Technical Indexes of Data Processors 11
1.3.4 The Evaluation of Data Processors 11
1.4 History and Present Situation of Research in Radar Data Processing Technology 12
1.5 Scope and Outline of the Book 14
2 Parameter Estimation 20
2.1 Introduction 20
2.2 The Concept of Parameter Estimation 20
2.3 Four Basic Parameter Estimation Techniques 23
2.3.1 Maximum A Posteriori Estimator 23
2.3.2 Maximum Likelihood Estimator 24
2.3.3 Minimum Mean Square Error Estimator 24
2.3.4 Least Squares Estimator 26
2.4 Properties of Estimators 26
2.4.1 Unbiasedness 26
2.4.2 The Variance of an Estimator 26
2.4.3 Consistent Estimators 26
2.4.4 Efficient Estimators 27
2.5 Parameter Estimation of Static Vectors 28
2.5.1 Least Squares Estimator 28
2.5.2 Minimum Mean Square Error Estimator 30
2.5.3 Linear Minimum Mean Square Error Estimator 32
2.6 Summary 33
3 Linear Filtering Approaches 34
3.1 Introduction 34
3.2 Kalman Filter 34
3.2.1 System Model 35
3.2.2 Filtering Model 41
3.2.3 Initialization of Kalman Filters 44
3.3 Steady-State Kalman Filter 48
3.3.1 Mathematical Definition and Judgment Methods for Filter Stability 49
3.3.2 Controllability and Observability of Random Linear System 49
3.3.3 Steady-State Kalman Filter 50
3.4 Summary 52
4 Nonlinear Filtering Approaches 53
4.1 Introduction 53
4.2 Extended Kalman Filter 53
4.2.1 Filter Model 54
4.2.2 Some Problems in the Application of Extended Kalman Filters 58
4.3 Unscented Kalman Filter 58
4.3.1 Unscented Transformation 59
4.3.2 Filtering Model 60
4.3.3 Simulation Analysis 61
4.4 Particle Filter 65
4.4.1 Filtering Model 65
4.4.2 Examples of the Application of EKF, UKF, and PF 67
4.5 Summary 71
5 Measurement Preprocessing Techniques 72
5.1 Introduction 72
5.2 Time Registration 72
5.2.1 Interpolation/Extrapolation Method Using Velocity 73
5.2.2 The Lagrange Interpolation Algorithm 74
5.2.3 Least-Squares Curve-Fitting Algorithm 74
5.3 Space Registration 75
5.3.1 Coordinates 75
5.3.2 Coordinate Transformation 80
5.3.3 Transformation of Several Common Coordinate Systems 83
5.3.4 Selection of Tracking Coordinate Systems and Filtering State Variables 87
5.4 Radar Error Calibration Techniques 88
5.5 Data Compression Techniques 89
5.5.1 Data Compression in Monostatic Radar 89
5.5.2 Data Compression in Multistatic Radar 91
5.6 Summary 93
6 Track Initiation in Multi-target Tracking 95
6.1 Introduction 95
6.2 The Shape and Size of Track Initiation Gates 96
6.2.1 The Annular Gate 96
6.2.2 The Elliptic/Ellipsoidal Gate 97
6.2.3 The Rectangular Gate 99
6.2.4 The Sector Gate 99
6.3 Track Initiation Algorithms 100
6.3.1 Logic-Based Method 101
6.3.2 Modified Logic-Based Method 102
6.3.3 Hough Transform-Based Method 103
6.3.4 Modified Hough Transform-Based Method 106
6.3.5 Hough Transform and Logic-Based Method 107
6.3.6 Formation Target Method Based on Clustering and Hough Transform 108
6.4 Comparison and Analysis of Track Initiation Algorithms 109
6.5 Discussion of Some Issues in Track Initiation 116
6.5.1 Main Indicators of Track Initiation Performance 116
6.5.2 Demonstration of Track Initiation Scan Times 116
6.6 Summary 117
7 Maximum Likelihood Class Multi-target Data Association Methods 118
7.1 Introduction 118
7.2 Track-Splitting Algorithm 118
7.2.1 Calculation of Likelihood Functions 119
7.2.2 Threshold Setting 120
7.2.3 Modified Likelihood Function 121
7.2.4 Characteristics of Track-Splitting Algorithm 122
7.3 Joint Maximum Likelihood Algorithm 123
7.3.1 Establishment of Feasible Partitions 123
7.3.2 Recursive Joint Maximum Likelihood Algorithm 125
7.4 0â"1 Integer Programming Algorithm 126
7.4.1 Calculation of the Logarithm Likelihood Ratio 126
7.4.2 0â"1 Linear Integer Programming Algorithm 128
7.4.3 Recursive 0â"1 Integer Programming Algorithm 129
7.4.4 Application of 0â"1 Integer Programming Algorithm 130
7.5 Generalized Correlation Algorithm 130
7.5.1 Establishing the Score Function 130
7.5.2 Application of the Generalized Correlation Algorithm 133
7.6 Summary 137
8 Bayesian Multi-target Data Association Approach 138
8.1 Introduction 138
8.2 Nearest-Neighbor Algorithm 138
8.2.1 Nearest-Neighbor Standard Filter 138
8.2.2 Probabilistic Nearest-Neighbor Filter Algorithm 139
8.3 Probabilistic Data Association Algorithm 141
8.3.1 State Update and Covariance Update 141
8.3.2 Calculation of the Association Probability 144
8.3.3 Modified PDAF Algorithm 146
8.3.4 Performance Analysis 147
8.4 Integrated Probabilistic Data Association Algorithm 152
8.4.1 Judgment of Track Existence 152
8.4.2 Data Association 154
8.5 Joint Probabilistic Data Association Algorithm 154
8.5.1 Basic Models of JPDA 155
8.5.2 Calculation of the Probability of Joint Events 160
8.5.3 Calculation of the State Estimation Covariance 162
8.5.4 Simplified JPDA Model 164
8.5.5 Performance Analysis 165
8.6 Summary 167
9 Tracking Maneuvering Targets 169
9.1 Introduction 169
9.2 Tracking Algorithm with Maneuver Detection 170
9.2.1 White Noise Model with Adjustable Level 171
9.2.2 Variable-Dimension Filtering Approach 172
9.3 Adaptive Tracking Algorithm 174
9.3.1 Modified-Input Estimation Algorithm 174
9.3.2 Singer Model Tracking Algorithm 176
9.3.3 Current Statistical Model Algorithm 180
9.3.4 Jerk Model Tracking Algorithm 182
9.3.5 Multiple Model Algorithm 184
9.3.6 Interacting Multiple Model Algorithm 186
9.4 Performance Comparison of Maneuvering Target Tracking Algorithms 189
9.4.1 Simulation Environment and Parameter Setting 189
9.4.2 Simulation Results and Analysis 191
9.5 Summary 201
10 Group Target Tracking 203
10.1 Introduction 203
10.2 Basic Methods for Track Initiation of the Group Target 204
10.2.1 Group Definition 204
10.2.2 Group Segmentation 205
10.2.3 Group Correlation 208
10.2.4 Group Velocity Estimation 209
10.3 The Gray Fine Track Initiation Algorithm for Group Targets 214
10.3.1 Gray Fine Association of Targets within the Group Based on the Relative Position Vector of the Measurement 215
10.3.2 Confirmation of the Tracks within a Group 220
10.3.3 Establishment of State Matrixes for Group Targets 221
10.3.4 Simulation Verification and Analysis of the Algorithm 221
10.3.5 Discussion 231
10.4 Centroid Group Tracking 233
10.4.1 Initiation, Confirmation, and Cancellation of Group Tracks 234
10.4.2 Track Updating 234
10.4.3 Other Questions 237
10.5 Formation Group Tracking 238
10.5.1 Overview of Formation Group Tracking 238
10.5.2 Logic Description of Formation Group Tracking 238
10.6 Performance Analysis of Tracking Algorithms for Group Targets 240
10.6.1 Simulation Environment 240
10.6.2 Simulation Results 240
10.6.3 Simulation Analysis 240
10.7 Summary 246
11 Multi-target Track Termination Theory and Track Management 250
11.1 Introduction 250
11.2 Multi-target Track Termination Theory 250
11.2.1 Sequential Probability Ratio Test Algorithm 250
11.2.2 Tracking Gate Method 252
11.2.3 Cost Function Method 253
11.2.4 Bayesian Algorithm 254
11.2.5 All-Neighbor Bayesian Algorithm 255
11.2.6 Performance Analysis of Several Algorithms 256
11.3 Track Management 258
11.3.1 Track Batch Management 258
11.3.2 Track Quality Management 266
11.3.3 Track File Management in the Information Fusion System 273
11.4 Summary 275
12 Passive Radar Data Processing 276
12.1 Introduction 276
12.2 Advantages of Passive Radars 276
12.3 Passive Radar Spatial Data Association 278
12.3.1 Phase Changing Rate Method 278
12.3.2 Doppler Changing Rate and Azimuth Joint Location 283
12.3.3 Doppler Changing Rate and Azimuth, Elevation Joint Location 285
12.3.4 Multiple-Model Method 286
12.4 Optimal Deployment of Direction-Finding Location 289
12.4.1 Area of the Position Concentration Ellipse 289
12.4.2 Derivation of the Conditional Extremum Based on the Lagrange Multiplier Method 292
12.4.3 Optimal Deployment by the Criterion that the Position Concentration Ellipse Area is Minimum 297
12.5 Passive Location Based on TDOA Measurements 299
12.5.1 Location Model 299
12.5.2 Two-Dimensional Condition 299
12.5.3 Three-Dimensional Condition 301
12.6 Summary 303
13 Pulse Doppler Radar Data Processing 304
13.1 Introduction 304
13.2 Overview of PD Radar Systems 304
13.2.1 Characteristics of PD Radar 304
13.2.2 PD Radar Tracking System 305
13.3 Typical Algorithms of PD Radar Tracking 307
13.3.1 Optimal Rangeâ"Velocity Mutual Coupling Tracking 309
13.3.2 Multi-target Tracking 312
13.3.3 Target Tracking with Doppler Measurements 312
13.4 Performance Analysis on PD Radar Tracking Algorithms 321
13.4.1 Simulation Environments and Parameter Settings 321
13.4.2 Simulation Results and Analysis 322
13.5 Summary 331
14 Phased Array Radar Data Processing 332
14.1 Introduction 332
14.2 Characteristics and Major Indexes 333
14.2.1 Characteristics 333
14.2.2 Major Indexes 334
14.3 Structure and Working Procedure 334
14.3.1 Structure 334
14.3.2 Working Procedure 335
14.4 Data Processing 336
14.4.1 Single-Target-in-Clutter Tracking Algorithms 337
14.4.2 Multi-target-in-Clutter Tracking Algorithm 343
14.4.3 Adaptive Sampling Period Algorithm 345
14.4.4 Real-Time Task Scheduling Strategy 349
14.5 Performance Analysis of the Adaptive Sampling Period Algorithm 355
14.5.1 Simulation Environment and Parameter Settings 355
14.5.2 Simulation Results and Analysis 356
14.5.3 Comparison and Discussion 360
14.6 Summary 361
15 Radar Network Error Registration Algorithm 362
15.1 Introduction 362
15.2 The Composition and Influence of Systematic Errors 362
15.2.1 The Composition of Systematic Errors 362
15.2.2 The Influence of Systematic Errors 363
15.3 Fixed Radar Registration Algorithm 366
15.3.1 Radar Registration Algorithm Based on Cooperative Targets 366
15.3.2 RTQC Algorithm 368
15.3.3 LS Algorithm 370
15.3.4 GLS Algorithm 371
15.3.5 GLS Algorithm in ECEF Coordinate System 373
15.3.6 Simulation Analysis 377
15.4 Mobile Radar Registration Algorithm 380
15.4.1 Modeling Method of Mobile Radar Systems 380
15.4.2 Mobile Radar Registration Algorithm Based on Cooperative Targets 386
15.4.3 Mobile Radar Maximum Likelihood Registration Algorithm 390
15.4.4 ASR Algorithm 397
15.4.5 Simulation Analysis 398
15.5 Summary 402
16 Radar Network Data Processing 405
16.1 Introduction 405
16.2 Performance Evaluation Indexes of Radar Networks 406
16.2.1 Coverage Performance Indexes 406
16.2.2 Target Capacity 407
16.2.3 Anti-jamming Ability 407
16.3 Data Processing of Monostatic Radar Networks 408
16.3.1 The Process of Data Processing of the Monostatic Radar Network 408
16.3.2 State Estimation of Monostatic Radar Networks 410
16.4 Data Processing of Bistatic Radar Networks 413
16.4.1 Basic Location Relation 413
16.4.2 Combined Estimation 416
16.4.3 An Analysis of the Feasibility of Combinational Estimation 417
16.5 Data Processing of Multistatic Radar Networks 420
16.5.1 Tracking Principle of Multistatic Radar Systems 421
16.5.2 Observation Equation of Multistatic Radar Network Systems 422
16.5.3 The Generic Data Processing Process of Multistatic Tracking Systems 422
16.6 Track Association 423
16.7 Summary 426
17 Evaluation of Radar Data Processing Performance 427
17.1 Introduction 427
17.2 Basic Terms 428
17.3 Data Association Performance Evaluation 429
17.3.1 Average Track Initiation Time 429
17.3.2 Accumulative Number of Track Interruptions 430
17.3.3 Track Ambiguity 431
17.3.4 Accumulative Number of Track Switches 432
17.4 Performance Evaluation of Tracking 432
17.4.1 Track Accuracy 433
17.4.2 Maneuvering Target Tracking Capability 434
17.4.3 False Track Ratio 434
17.4.4 Divergence 435
17.5 Evaluation of the Data Fusion Performance of Radar Networks 436
17.5.1 Track Capacity 436
17.5.2 Detection Probability of Radar Networks 436
17.5.3 Response Time 437
17.6 Methods of Evaluating Radar Data Processing Algorithms 438
17.6.1 Monte Carlo Method 438
17.6.2 Analytic Method 438
17.6.3 Semi-physical Simulation Method 439
17.6.4 Test Validation Method 440
17.7 Summary 440
18 Radar Data Processing Simulation Technology 441
18.1 Introduction 441
18.2 Basis of System Simulation Technology 442
18.2.1 Basic Concept of System Simulation Technology 442
18.2.2 Digital Simulation of Stochastic Noise 444
18.3 Simulation of Radar Data Processing Algorithms 449
18.3.1 Simulation of Target Motion Models 449
18.3.2 Simulation of the Observation Process 452
18.3.3 Tracking Filtering and Track Management 453
18.4 Simulation Examples of Algorithms 457
18.5 Summary 463
19 Practical Application of Radar Data Processing 464
19.1 Introduction 464
19.2 Application in ATC Systems 464
19.2.1 Application, Components, and Requirement 464
19.2.2 Radar Data Processing Structure 466
19.2.3 ATC Application 467
19.3 Application in Shipboard Navigation Radar 474
19.4 Application in Shipboard Radar Clutter Suppression 476
19.4.1 Principle of Clutter Suppression in Data Processing 476
19.4.2 Clutter Suppression Method through Shipboard Radar Data Processing 477
19.5 Application in Ground-Based Radar 480
19.5.1 Principle of Data Acquisition 480
19.5.2 Data Processing Procedure 481
19.6 Applications in Shipboard Monitoring System 482
19.6.1 Application, Components, and Requirement 482
19.6.2 Structure of the Marine Control System 483
19.7 Application in the Fleet Air Defense System 484
19.7.1 Components and Function of the Aegis Fleet Air Defense System 484
19.7.2 Main Performance Indexes 485
19.8 Applications in AEW Radar 486
19.8.1 Features, Components, and Tasks 486
19.8.2 Data Processing Technology 487
19.8.3 Typical Working Mode 489
19.9 Application in Air Warning Radar Network 492
19.9.1 Structure of Radar Network Data Processing 492
19.9.2 Key Technologies of Radar Network Data Processing 493
19.10 Application in Phased Array Radar 495
19.10.1 Functional Features 495
19.10.2 Data Processing Procedure 495
19.10.3 Test Examples 496
19.11 Summary 498
20 Review, Suggestions, and Outlook 499
20.1 Introduction 499
20.2 Review of Research Achievements 499
20.2.1 The Basis of State Estimation 499
20.2.2 Measurement Preprocessing Technology 500
20.2.3 Track Initiation in Multi-target Tracking 500
20.2.4 Multi-target Data Association Method 500
20.2.5 Maneuvering Target and Group Tracking 500
20.2.6 Multi-target Tracking Termination Theory and Track Management 501
20.2.7 System Error Registration Issue 501
20.2.8 Performance Evaluation of Radar Data Processors 501
20.2.9 Simulation Technology of Radar Data Processing 501
20.2.10 Applications of Radar Data Processing Techniques 502
20.3 Issues and Suggestions 502
20.3.1 The Application of Data Processing Technology in Other Sensors 502
20.3.2 Track Initiation in Passive Sensor Tracking 502
20.3.3 Non-Gaussian Noise 503
20.3.4 Data Processing in Non-standard and Nonlinear Systems 503
20.3.5 Data Processing in Multi-radar Networks 503
20.3.6 Joint Optimization of Multi-target Tracking and Track Association 503
20.3.7 Comprehensive Utilization of Target Features and Attributes in Multi-radar Tracking 504
20.3.8 Comprehensive Optimization of Multi-radar Information Fusion Systems 504
20.3.9 Tracking Multi-targets in Complex Electromagnetic Waves and Dense Clutter 504
20.4 Outlook for Research Direction 505
20.4.1 Information Fusion and Control Integration Technology of Multi-radar Networks 505
20.4.2 Joint Optimization of Target Tracking and Identification 505
20.4.3 Integration Technology of Search, Tracking, Guidance, and Command 505
20.4.4 Multi-radar Resource Allocation and Management Technology 505
20.4.5 Database and Knowledge Base Technology in Radar Data Processing 506
20.4.6 Engineering Realization of Advanced Radar Data Processing Algorithms 506
20.4.7 High-Speed Calculation and Parallel Processing Technology 506
20.4.8 Establishment of System Performance Evaluation Methods and Test Platforms 506
20.4.9 Common Theoretical Models for Variable Structure State Estimation 506
20.4.10 Automatic Tracking of Targets in Complex Environments 507
20.4.11 Tracking and Invulnerability of Multi-radar Network Systems 507
References 508
Index 523
