Design and analysis of modern tracking systems:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boston [u.a.]
Artech House
1999
|
| Schriftenreihe: | Artech House radar library
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXXI, 1230 S. graph. Darst. |
| ISBN: | 1580530060 9781580530064 |
Internformat
MARC
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| 020 | |a 1580530060 |c alk. paper |9 1-58053-006-0 | ||
| 020 | |a 9781580530064 |9 978-1-58053-006-4 | ||
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| 100 | 1 | |a Blackman, Samuel S. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Design and analysis of modern tracking systems |c Samuel Blackman; Robert Popoli |
| 246 | 1 | 3 | |a Modern tracking systems |
| 264 | 1 | |a Boston [u.a.] |b Artech House |c 1999 | |
| 300 | |a XXXI, 1230 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Artech House radar library | |
| 650 | 7 | |a Radar de poursuite |2 ram | |
| 650 | 7 | |a cinématique |2 inriac | |
| 650 | 7 | |a filtrage |2 inriac | |
| 650 | 7 | |a fusion donnée |2 inriac | |
| 650 | 7 | |a performance système |2 inriac | |
| 650 | 7 | |a poursuite multi-cible |2 inriac | |
| 650 | 7 | |a système détection |2 inriac | |
| 650 | 4 | |a Tracking radar | |
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| 650 | 0 | 7 | |a Zielverfolgungsradar |0 (DE-588)4590902-7 |2 gnd |9 rswk-swf |
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Datensatz im Suchindex
| _version_ | 1804132812974981120 |
|---|---|
| adam_text | Design and Analysis of Modern
Tracking Systems
Samuel Blackman
Robert Popoli
Artech House
Boston • London
Contents
Preface xxvii
Acknowledgments xxxi
1 The Basics of Target Tracking 1
1 1 Introduction 1
1 2 Basic Processing Definitions 4
1 3 Elements of a Conventional MTT System 5
131 Measurement Data Processing 6
132 Data Association 8
133 Filtering and Prediction 11
1 4 Overview of Data Association Issues and
Methodologies 12
141 Interpretation and Issues 12
142 Unique-Neighbor Versus All-Neighbors
Data Association 15
143 Sequential Versus Deferred Decision
Logic 16
144 Incorporation of Group Information 17
145 Use of Thresholding 18
146 State Estimation Without Explicit Data
Association 19
1 5 Multiple Sensor Considerations 19
1 6 System Design Issues 21
161 Joint Sensor/Tracking System Design 22
162 Performance Evaluation 23
VII
Design and Analysis of Modern Tracking Systems
viii
1 7 Related Background Reading 24
References 24
2 Sensor and Source Characteristics 29
2 1 Preliminaries 32
211 Kinematic Measurements 32
212 Attribute Measurements 33
213 Signal-to-Interference Ratio and
Measurement Availability and Quality 33
2 2 Tracking Radar Sensor Systems 36
221 Radar Sensor Overview 36
222 Measurement Availability 39
223 Measurement Quality 68
224 False Measurements and Other
Measurement Disturbances 73
225 Further Measurement Signal Characteristics 76
226 Sensor Agility 80
227 Sensor Management Information 81
2 3 Infrared Search and Track Systems 85
231 Electro-Optical Sensor Overview 85
232 IRST Sensor Overview 86
233 The Nature of IR Radiation 89
234 Target Energy 94
235 Energy Propagation and Atmospheric Effects 100
236 Background Energy 104
237 Measurement Availability 107
238 Increasing Measurement Availability With
Signal Processing 112
239 Kinematic Measurement Accuracy 115
2 3 10 Attribute Measurement Capabilities 115
2 3 11 Sensor Artifacts 117
2 3 12 IR Processing Chain 117
2 4 Electronic Support Measures Sensor Systems 119
241 ESM Sensor Overview 119
242 ESM Sensor Signal Processing 121
243 ESM Measurement Availability 122
244 ESM Measurement Utilization and
Interpretation 123
2 5 Laser Sensor Tracking Systems 124
251 Laser Sensor Overview 124
Contents
IX
252 Laser Sensor Measurements 124
253 Laser Sensor System Applications 127
2 6 Bistatic Radar Tracking Systems 128
261 Bistatic Radar Overview 128
262 Bistatic Radar Measurements 130
263 Bistatic Radar Tracking 131
2 7 Acoustic Sensor Tracking Systems 131
271 Acoustic Sensor Overview 131
272 Acoustic Sensor Measurement 133
2 8 Warning Sensor Systems 134
References 136
Appendix 2A: Radar Po and Pfa
Calculations 141
3 Kinematic State Estimation: Filtering
and Prediction 147
3 1 Introduction 147
3 2 Least Squares Estimation 148
321 Linear Least Squares 148
322 Nonlinear Least Squares Estimation 151
323 Recursive Least Squares 155
324 Observability 157
3 3 Kalman Filtering 157
331 Kalman Filter Definition 158
332 Correspondence Between Kalman and
Fixed-Gain Filters 160
333 Example of a Two-State Kalman Filter 161
334 System Driving Noise and Maneuver Model 163
3 4 Extended Kalman Filtering 164
3 5 Example Comparing Nonlinear Estimation
Performance 168
351 Problem and Method Definitions 168
352 Results 170
3 6 Nonlinear Filtering With
Pseudomeasurements 172
3 7 Choice of Tracking Coordinate System 174
371 Choice of Origin and Axes 174
372 Cartesian Coordinate Tracking 178
373 Spherical/Sensor Coordinate Tracking 182
374 Cartesian Angle-Only Filtering 187
X
Design and Analysis of Modern Tracking Systems
3 8 Filter Simplification 189
381 State Reduction 189
382 Filter Decoupling 191
3 9 Conclusions and Future Directions 193
References 195
4 Modeling and Tracking Dynamic Targets 199
4 1 Introduction 199
4 2 Target Dynamic Models 200
421 Singer Acceleration Model 200
422 White Noise Constant Velocity and
Constant Acceleration Dynamic Models 203
423 Coordinated Turn Models 205
424 Other Target Dynamic Modeling Approaches 207
4 3 Kalman Filter Implementation 208
431 Horizontal Turn Model With Velocity States 209
432 Implementation of Pseudomeasurements 211
433 Nearly Constant Speed Horizontal Turn
Model 212
4 4 Maneuver Adaptive Filtering Methods 214
441 Single Filter Reactive Adaptation 214
442 Variable Dimension Filtering 216
443 Cascaded Filtering 216
444 Multiple Model Filtering 221
4 5 Interacting Multiple Model Filtering 221
451 IMM Interaction/Mixing and Prediction 224
452 Gating and Data Association 225
453 Likelihood Calculation and Model
Probability Update 226
454 Combining Different State Models 227
455 Choice of Markov Transition Probabilities 229
456 Alternative Mixing Procedures 232
4 6 Comparative Performance Study 232
461 Choice of Methods to Compare 233
462 Results 235
4 7 Three-Dimensional Models 240
4 8 Tracking Tactical Ballistic Missile
Targets 241
481 Boost-Stage Missile Dynamics Model 242
482 Boost-Stage Filter Development 24
Contents
XI
483 Multiple Model Approach 247
4 9 Conclusions 251
References 253
5 Passive Sensor Tracking Methods 259
5 1 Introduction 259
5 2 Initial Orbit Determination 262
521 Derivation of Laplace Method for IOD 262
522 Example Results 264
523 Methods to Reduce IOD Error 267
5 3 State Estimation With Angle-Only
Measurements and Ownship Maneuver 268
531 Cartesian Filtering Approach 269
532 Modified Polar and Spherical Coordinates
Filter Approach 271
533 Comparative Simulation Results 275
5 4 Tracking With Frequency (Doppler)
and Angle Measurement Data 280
541 Extension of MPC to Frequency/Doppler
Measurements 282
542 Cartesian Coordinate State Estimation Using
Angle and Frequency/Doppler Measurements 283
5 5 Use of Measured IR Intensity 286
551 Time-to-Go Estimation From Amplitude
Rate Tracking 286
552 Single Sensor Multispectral Ranging 290
5 6 Use of Template/Profile Data to Determine
Target Type and Boost-Stage Trajectory 293
561 Overview of Profile Matching Procedure 294
562 Iterative Search Procedure 299
563 Use of Measured Intensity 302
5 7 Target Image Tracking (Extended Target
Tracking) 303
571 Algorithm Elements 304
572 Centroid and Edge Tracking 309
573 Correlation Tracking 310
574 Filtering and Data Association 313
575 Laser Augmented Image Target Tracking 315
5 8 Video Sensor Traffic Monitoring 315
581 Vehicle Detection 316
XIV
Design and Analysis of Modern Tracking Systems
751 Mixture Reduction Algorithms 428
752 Multiple Scan JPDA 431
7 6 Augmented State Vector Approach to MTT 433
761 Coupling Due to Common Target Dynamics
and Measurement Error 433
762 Image Tracking of Crossing Targets 439
7 7 State Estimation Without Data Association 440
771 The Symmetric Measurement Equation Filter 440
772 Event-Averaged Maximum Likelihood
Estimation 445
773 Batch Processing Maximum Likelihood
Estimation Methods 450
774 Bayesian State Space Estimation 451
7 8 Track-Befo re- Detect 455
7 9 Knowledge-Based Methods 458
791 Neural Network Applications 458
792 Genetic Algorithms 463
793 Use of Qualitative/Heuristic Information 469
7 10 Conclusions 473
References 475
8 Attribute Data Fusion 48
8 1 Introduction 48
811 The Role of Attribute Data Fusion 48
812 Comments on Selecting an Inferencing
Approach 48
813 Chapter Overview 48
8 2 The ID Problem and the Nature
of Available A Priori Information 48
821A Priori Target ID Modeling 48
822 Target Attribute Dynamics Modeling 48
823 Measurement Process Modeling 48
8 3 Voting or Set Intersection Techniques
for Attribute Data Fusion 49
8 4 Classical Statistical Methods 49
841 Bayesian Inference 49
842 Maximum A Posteriori Inference
and the MAP Techniques 50
843 Likelihood Inferencing and the Maximum
Likelihood Technique 50
Contents
xv
8 5 Evidential Reasoning for Attribute Data
Fusion 507
851 Evidential Reasoning Primer 509
852 Implementation of Evidential Reasoning 513
853 Partial Probability Models 514
854 Partial Probability Models and Evidential
Reasoning 517
855 Bayes’s Rule With Parametric Probability
Models and Relation to Dempster’s Rule
of Combination 521
856 Partial Transitional Probability Models
for Evidential ID Techniques 533
857 Power Set Approach 544
858 Typical Set Approach 547
859 Comparative Example of Bayesian
and Evidential Reasoning
for Target ID 551
8 6 More on the Relation Between Evidential
Reasoning and Probability 564
861 Basic Mass Assignment Procedure
for Complete Transitional Models 565
862 Correspondence Between Bayesian and
Evidential Reasoning Under Complete
Probability Models 567
863 Three Prisoner Problem Example Under
Complete Probability Models 569
864 Correspondence Between Bayesian and
Evidential Reasoning Under Complete
Transitional and Partial Prior Probability
Models 570
865 Relation of Lower and Upper Probabilities
to the Support and Plausibility 574
866 Three Prisoner Problem Example Under
Partial Probability Models 575
8 7 Implementing Dempster-Shafer Reasoning 578
8 8 Conclusions 578
References 582
Appendix 8A: Derivation of Maximum
and Minimum Bayesian A Posteriori
Probabilities Under Partial Prior Distributions 585
XVI
Design and Analysis of Modern Tracking Systems
9 Multiple Sensor Tracking: Issues and Methods 595
9 1 Introduction 595
9 2 Basic Principles of Multiple Sensor Tracking
System Design 598
9 3 Multiple Sensor System Architectures 599
931 Central-Level Tracking, Centralized
Track File 602
932 Central-Level Tracking, Distributed
Track File 607
933 Sensor-Level Tracking, Centralized Track File 608
934 Sensor-Level Tracking, Distributed Track File 610
935 Hybrid System 611
9 4 Application Examples 612
941 Multiple Passive Sensor System Tracking 612
942 Internetted Multisensor Systems 613
9 5 General Expression for Multisensor Data
Association 616
951 Derivation 616
952 Examples 620
953 Generalized Assignment Matrix 624
9 6 Multisensor Data Association Methods 626
961 Centralized Architectures 626
962 Distributed Architectures 627
963 Overview of Track-to-Track Association 628
964 Implementations of Track-to-Track
Association 629
965 Extension to MHT and JPDA 637
9 7 Distributed Multisensor Detection and
Track Initiation 637
971 Global Detection Test 639
972 System Detection Performance Optimization 641
973 Information Transmission to the Fusion
Center 643
974 Other Issues in Multisensor Detection 645
975 Multiple Sensor Track Confirmation 646
9 8 Multiple Sensor Filtering 649
981 Handling Differing Rates/Out-of-Sequence
Data 649
982 Ensuring That More Is Better 650
983 Use of Complementary Sensor Data 650
Contents
XVII
9 9 10 Conclusions and Further Reading References Multiple Sensor Tracking: System Implementation and Applications 651 654 661
10 1 Introduction 661
10 2 Multiple Sensor Measurement
Transformation 662
10 2 1 The Stereographic Coordinate System 663
10 2 2 Nonlinear Measurement Input Form 665
10 3 Central-Level Track Filtering 667
10 3 1 Alternative Central-Level Track Updating
Methods 667
10 3 2 Filtering Out-of-Sequence Observations:
Optimal Filter Development 670
10 4 Multiple Sensor Track Fusion 678
10 4 1 Fusion Methods/Error Sources 678
10 4 2 Use of Cross Covariance 681
10 4 3 Use of Equivalent Measurements 684
10 5 Multiple Sensor Registration/Misalignment
Estimation 689
10 5 1 Registration Error Sources 689
10 5 2 Matching Method to Application 692
10 5 3 Least Squares Estimation Approach 692
10 5 4 Registration Error Estimation via Kalman
Filtering 696
10 5 5 Combined Registration and Data Association 697
10 6 Distributed Multiple Passive Sensor Systems 699
10 6 1 Choice of Tracking Architecture 700
10 6 2 State Estimation Using Distance of Closest
Approach 702
10 6 3 Triangulation Gating and Association
Statistics 706
10 6 4 Estimation Accuracy 711
10 6 5 Varad Hinge (Inclination) Angle Method 716
10 7 Angle-Only (2D)-to-Position (3D) Track
Gating and Fusion 719
10 7 1 Gating and Fusion Relationships 719
10 7 2 Gating and Fusion Example 722
10 8 Stereo Track Formation and Maintenance 724
Design and Analysis of Modern Tracking Systems
xviii
10 8 1 Angle-Only Tracking Deghosting Problem 725
10 8 2 Deghosting for Closely Spaced Ballistic
Targets 728
10 9 Conclusions 729
References 730
Appendix 1OA: Derivation of Hinge Angle
Statistics 735
11 Reasoning Schemes for Situation Assessment
and Sensor Management 737
11 1 Introduction 737
11 2 An Introduction to Fuzzy Set Theory
and Inexact Reasoning Systems 739
11 21A Fuzzy Set Primer 740
11 2 2 Rule-Based Systems and Inexact
Reasoning 742
11 2 3 Implementing Inexact Reasoning 743
11 3 Introduction to More Sophisticated Fuzzy
Set Theory 746
11 4 Some Preliminaries 746
11 5 T-Norms, T-Conorms, and Negation
Operators 748
11 6 The Extension Principle 753
11 7 Relations, Composition, and Partial
Orderings 756
11 7 1 Fuzzy Relation Basics and Composition 756
11 7 2 Fuzzy Partial Ordering 760
11 8 Linguistic Variables and Linguistic
Approximation 767
11 9 Implication and Inferencing 768
11 10 Ranking Objects Using Fuzzy Partial
Orderings 776
11 11 Fuzzy State Machines 781
11 12 Conclusions 794
References 794
12 Situation Assessment 797
12 1 Introduction 797
12 1 1 The Role of Situation Assessment 798
12 1 2 Chapter Organization 801
Contents
XIX
12 2 Domain-Specific Knowledge of Weapon
Systems 801
12 2 1 Overview of Tactical Missile Guidance 802
12 2 2 Missile Delivery Methods 802
12 2 3 Missile Guidance Laws 804
12 2 4 Tactical Missile Launch Envelopes 808
12 3 Domain-Specific Knowledge of Tactical
Intercepts 811
12 3 1 Basic Concepts of Tactical Intercepts 812
12 3 2 Forward Quarter Intercept 814
12 3 3 Stern Conversion Intercept 821
12 3 4 Variations on the Forward Quarter
and the Stern Conversion Intercepts 821
12 4 Situation Assessment System Architecture 832
12 4 1 Situation Assessment Data Processing Block
Diagram 833
12 5 Simple or Static Recognition 837
12 6 Temporal Recognition or Capturing Tactical
Intercept Domain-Specific Knowledge 845
12 6 1 Automated Temporal Recognition
of Tactical Air Intercepts 847
12 6 2 Temporal Reasoning as a Methodology
for Event Fusion 849
12 7 Partial Ordering and Prioritization 852
12 8 Ancillary Situation Assessment Functions 860
12 9 Conclusions 862
References 863
13 Tracking System Performance Prediction
and Evaluation 865
13 1 Introduction 865
13 2 Tracking Filter Performance Prediction 866
13 3 Predicting Track Confirmation Performance 871
13 3 1 Limits on Track Confirmation Feasibility 872
13 3 2 Application of SPRT to Track Confirmation 873
13 3 3 SPRT Analysis of Track Confirmation 874
13 3 4 Simplified Monte Carlo Simulation 877
13 3 5 IRST Example 878
13 4 Analytical Expressions for Predicting Data
Association Performance 882
XX
Design and Analysis of Modern Tracking Systems
13 4 1 Probability of Correct Association/Decision 88
13 4 2 Probability of Resolution 88
13 5 Generalizing Covariance Analysis to Include
Data Association 89
13 5 1 Generalized Covariance Equation 89
13 5 2 Application of Generalized Covariance
Analysis 89
13 5 3 Predicting Fundamental Limits (Computing
Cramer-Rao Bounds for MTT) 89
13 6 MTT System Evaluation Metrics 89
13 6 1 Track-to-Truth Assignment 89
13 6 2 Computation of Track Statistics 90
13 6 3 Measures of Effectiveness 90
13 64A Taxonomy of Target Tracks 90
13 6 5 Implementation Issues 90
13 7 Conclusions 90
References 90
14 Multiple Target Tracking With an Agile
Beam Radar 91
14 1 Introduction 91
14 2 Detection: Observation Generation
and Processing 91
14 2 1 Enhancing Detection and Measurement
Performance 91
14 2 2 Reducing the Effects of Jet Engine
Modulation 91
14 3 Efficient Search for New Targets 91
14 3 1 Trade-Off Issues 91
14 3 2 Example Search Allocation Optimization 91
14 4 Track Update Resource Allocation 92
14 4 1 Minimizing Track Update Resource
Allocation Requirements 92
14 4 2 Simulation of Track Update Resource
Allocation 92
14 4 3 Update of High-Priority Targets 93
14 4 4 Target Cross-Section Estimation 93
14 5 Allocation Among Multiple Functions 93
14 5 1 Determining Task Figures of Merit 93
14 5 2 Scheduling Methodology 93
Contents
xxi
14 5 3 Other Allocation Issues 937
14 6 Filtering and Prediction 941
14 6 1 Choice of Tracking Coordinates and States 941
14 6 2 Tracking Filters for Maneuvering Targets 942
14 6 3 Adaptive Sampling Methods 942
14 7 Data Association 943
14 7 1 Conventional Data Association 944
14 7 2 Multiple Hypothesis Tracking 944
14 7 3 Joint Probabilistic Data Association 945
14 7 4 Group Tracking 945
14 7 5 Other Data Association Issues 945
14 8 Results From Benchmark Tracking Problem 946
14 8 1 Data Association Conclusions 949
14 8 2 Filtering Conclusions 950
14 8 3 Resource Allocation Conclusions 951
14 8 4 Allocation Robustness to Target Maneuvers 952
14 9 Combining IRST and Agile Beam Radar Data 954
14 9 1 Increased Track Confirmation Range 955
14 9 2 Multisensor Resource Allocation 955
14 10 Conclusions 958
References 959
Appendix 14A: Expected Power Loss Due
to Track Offset From Antenna Pointing Angle 963
15 Sensor Management 967
15 1 Introduction 967
15 1 1 Chapter Goals 968
15 1 2 Related Studies 971
15 1 3 Chapter Scope and Organization 973
15 2 Exploring the Sensor Management Imperative 974
15 2 1 The Role of Sensor Management 974
15 2 2 Cataloging the Sensor Management
Imperative 977
15 2 3 Addressing the Sensor Management
Imperative 982
15 3 Understanding What Is to Be Managed 983
15 3 1 Two Views of Managing Sensors 983
15 3 2 Parameter View of What Is to Be Managed 984
15 3 3 Mode View of What Is to Be Managed 987
15 3 4 Closing Remarks 995
xxii Design and Analysis of Modern Tracking Systems
15 4 Understanding What Is to Be Optimized 995
15 4 1 Role of Tracking System Figures of Merit
in Sensor Management Optimization 996
15 4 2 Target Acquisition Figures of Merit 997
15 4 3 Other Figures of Merit 1003
15 5 Sensor Management Implementation
Issues and Principles 1004
15 5 1 Architecture for Sensor Management 1005
15 5 2 The Macro/Micro Architecture 1006
15 5 3 Scheduling Techniques 1009
15 5 4 Decision-Making Techniques 1014
15 5 5 Overview of a Prototype Implementation
of Sensor Management 1015
15 5 6 Overview of Prototype Implementation
of Macro Sensor Management 1018
15 5 7 Overview of Prototype Implementation
of Micro Sensor Management 1029
15 5 8 An Illustrative Example of the Sensor
Management Process 1039
15 5 9 Overview of Sensor Management Operation 1044
15 6 Policies of Operation 1053
15 6 1 Example of Policies of Operation
for Synergistic Sensor Utilization 1055
15 6 2 Some Important Policies 1060
15 7 Distributed IR Sensor System Management 1063
15 7 1 System Overview 1063
15 7 2 Macro Commands 1064
15 7 3 Micro Sensor Management 1064
15 8 Conclusions 1065
References 1065
16 Multiple Hypothesis Tracking System
Design and Application_______________________1069
16 1 Introduction 1069
16 2 MHT Algorithm Description 1070
16 2 1 Track Formation and Maintenance 1071
16 2 2 Track-Level Pruning and Confirmation 1072
16 2 3 Clustering 1072
16 2 4 Hypothesis Formation and Pruning 1073
16 2 5 Global-Level Track Pruning 1074
Contents
xxiii
16 2 6 Track Updating and Merging 1074
16 2 7 User Presentation Logic 1075
16 3 Track and Hypothesis Scoring
and Probability Computations 1075
16 4 Presentation of MHT Data 1076
16 4 1 Coordinated Presentation of MHT Data 1077
16 4 2 Continuous-Time Representation of MHT
Data 1080
16 5 Ensuring MHT Computational Feasibility 1083
16 5 1 Gating and Filtering Efficiencies 1083
16 5 2 Track Branch Limiting/Pruning 1084
16 5 3 Bilevel Processing 1086
16 5 4 Fail-Safe Logic 1086
16 5 5 Parallel Processing 1087
16 5 6 Timing/Sizing Results 1089
16 6 Combining MHT and IMM Filtering 1090
16 6 1 Alternative IMM/MHT System Methods 1090
16 6 2 An IMM/MHT Implementation 1092
16 6 3 Comparative Results 1093
16 7 Multiradar Air Defense System Application 1096
16 7 1 System Description 1096
16 7 2 Handling Multiradar Asynchronous Data 1096
16 7 3 Handling Different Measurement
Information Content 1098
16 7 4 False Target Density, Track Confirmation,
and Maintenance 1099
16 8 MHT Compensation for Possibly
Unresolved Measurements 1100
16 81A Priori MHT Hypotheses Augmentation 1101
16 8 2 Bayesian PDF Propagation Method 1102
16 83A Posteriori MHT Hypothesis Augmentation 1103
16 8 4 MHT With Group and Object Tracking 1103
16 9 MHT Applications to Agile Beam Radar 1104
16 9 1 MHT-Based Agile Beam Radar Allocation 1105
16 9 2 Track Score Computation 1106
16 9 3 IMM/MHT Application to Agile Beam
Radar Benchmark Problem 1106
16 10 MHT Applied to Agile Beam
Radar/IRST Trac dng 1108
16 10 1 IRST Sensor-Level Tracker 1109
XXIV
Design and Analysis of Modern Tracking Systems
16 10 2 Central-Level MHT Tracker 111
16 11 Conclusions 1111
References 1111
17 Detection and Tracking of Dim Targets
in Clutter 111
17 1 Introduction 111
17 2 Signal Processing Methods for Detecting
Dim Targets 111
17 2 1 Maximum Likelihood/Matched Filter
Detection 111
17 2 2 Adaptive Detection 112
17 2 3 Signal Integration Along Target Paths 112
17 2 4 Sequential Detection 112
17 2 5 Nonlinear Detection and Feature Utilization 112
17 3 Data Association Methods 112
17 3 1 Multiscan Processing 113
17 3 2 MHT 113
17 3 3 JPDA 1131
17 4 System Performance Optimization
and Implementation 1132
17 4 1 SNR Contribution to Score Function 1133
17 4 2 Optimization of Signal Contribution 113
17 4 3 Signal Processing Versus Tracking Resource
Allocation Issues 1141
17 4 4 IR Clutter Track Suppression 1142
17 4 5 Use of All MHT Branches 1143
17 5 Track-Before-Detect 1144
17 5 1 Hough Transform Application to TBD 1145
17 5 2 DPA Implementation of TBD 1148
17 5 3 Noncellular TBD 1153
17 6 Track Confirmation Comparison Example 1154
17 6 1 Study Description 1154
17 6 2 Results 1156
17 7 Two-Stage Detection and Tracking 1158
17 7 1 Use of Segments for Track Update 1158
17 7 2 Application of Equivalent Measurements 1159
17 8 Multiple Sensor Applications 1160
17 8 1 Overview of Potential Architectures/Methods 1160
17 8 2 Proposed Multisensor Architecture 1163
Contents
xxv
17 9 Conclusions 1164
References 1165
Appendix 17A: Target Anomaly Detection
Using Combined Space and Spectral Filtering 1172
Appendix 17B: Determination of Tracker
SNR Gain 1174
Acronyms and Abbreviations_____________________1177
About the Authors 1183
Index
|
| any_adam_object | 1 |
| author | Blackman, Samuel S. Popoli, Robert |
| author_facet | Blackman, Samuel S. Popoli, Robert |
| author_role | aut aut |
| author_sort | Blackman, Samuel S. |
| author_variant | s s b ss ssb r p rp |
| building | Verbundindex |
| bvnumber | BV019372851 |
| callnumber-first | T - Technology |
| callnumber-label | TK6580 |
| callnumber-raw | TK6580 |
| callnumber-search | TK6580 |
| callnumber-sort | TK 46580 |
| callnumber-subject | TK - Electrical and Nuclear Engineering |
| classification_rvk | ZN 6500 |
| classification_tum | ELT 733f |
| ctrlnum | (OCoLC)41165377 (DE-599)BVBBV019372851 |
| dewey-full | 621.3848 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 621 - Applied physics |
| dewey-raw | 621.3848 |
| dewey-search | 621.3848 |
| dewey-sort | 3621.3848 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Elektrotechnik Elektrotechnik / Elektronik / Nachrichtentechnik |
| format | Book |
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| id | DE-604.BV019372851 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T19:58:47Z |
| institution | BVB |
| isbn | 1580530060 9781580530064 |
| language | English |
| lccn | 99027662 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-012836212 |
| oclc_num | 41165377 |
| open_access_boolean | |
| owner | DE-91G DE-BY-TUM DE-739 DE-706 DE-573 DE-11 DE-29T DE-1050 |
| owner_facet | DE-91G DE-BY-TUM DE-739 DE-706 DE-573 DE-11 DE-29T DE-1050 |
| physical | XXXI, 1230 S. graph. Darst. |
| publishDate | 1999 |
| publishDateSearch | 1999 |
| publishDateSort | 1999 |
| publisher | Artech House |
| record_format | marc |
| series2 | Artech House radar library |
| spelling | Blackman, Samuel S. Verfasser aut Design and analysis of modern tracking systems Samuel Blackman; Robert Popoli Modern tracking systems Boston [u.a.] Artech House 1999 XXXI, 1230 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Artech House radar library Radar de poursuite ram cinématique inriac filtrage inriac fusion donnée inriac performance système inriac poursuite multi-cible inriac système détection inriac Tracking radar Objektverfolgung (DE-588)4311226-2 gnd rswk-swf Zielverfolgungsradar (DE-588)4590902-7 gnd rswk-swf Objektverfolgung (DE-588)4311226-2 s Zielverfolgungsradar (DE-588)4590902-7 s DE-604 Popoli, Robert Verfasser aut HEBIS Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012836212&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Blackman, Samuel S. Popoli, Robert Design and analysis of modern tracking systems Radar de poursuite ram cinématique inriac filtrage inriac fusion donnée inriac performance système inriac poursuite multi-cible inriac système détection inriac Tracking radar Objektverfolgung (DE-588)4311226-2 gnd Zielverfolgungsradar (DE-588)4590902-7 gnd |
| subject_GND | (DE-588)4311226-2 (DE-588)4590902-7 |
| title | Design and analysis of modern tracking systems |
| title_alt | Modern tracking systems |
| title_auth | Design and analysis of modern tracking systems |
| title_exact_search | Design and analysis of modern tracking systems |
| title_full | Design and analysis of modern tracking systems Samuel Blackman; Robert Popoli |
| title_fullStr | Design and analysis of modern tracking systems Samuel Blackman; Robert Popoli |
| title_full_unstemmed | Design and analysis of modern tracking systems Samuel Blackman; Robert Popoli |
| title_short | Design and analysis of modern tracking systems |
| title_sort | design and analysis of modern tracking systems |
| topic | Radar de poursuite ram cinématique inriac filtrage inriac fusion donnée inriac performance système inriac poursuite multi-cible inriac système détection inriac Tracking radar Objektverfolgung (DE-588)4311226-2 gnd Zielverfolgungsradar (DE-588)4590902-7 gnd |
| topic_facet | Radar de poursuite cinématique filtrage fusion donnée performance système poursuite multi-cible système détection Tracking radar Objektverfolgung Zielverfolgungsradar |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012836212&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT blackmansamuels designandanalysisofmoderntrackingsystems AT popolirobert designandanalysisofmoderntrackingsystems AT blackmansamuels moderntrackingsystems AT popolirobert moderntrackingsystems |