Radar data processing . Volumel , Introduction and tracking

목차 (Table of Contents)

• CONTENTS
• Acknowledgements = xvii
• Glossary of Notation = xix
• 1. INTRODUCTION = 1
• 1.1 DATA PROCESSING IN RADAR SYSTEMS = 1
• 1.1.1 Radar Classification = 1
• 1.1.2 An Overview of Radar Techniques = 5
• 1.1.3 The Track-While-Scan Radar System Concept = 12
• 1.2 DATA PROCESSING IN PHASED-ARRAY RADAR = 19
• 1.2.1 Electronically Steered Phased-Array Antenna = 19
• 1.2.2 Use of the Phased-Array Antenna in Radar systems = 24
• 1.2.3 The Controller = 24
• 1.2.4 The Trackinfg Function = 28
• 1.3 DATA PROCESSING IN NETTED RADAR = 32
• 1.3.1 Examples of Netted Radar Systems = 34
• 1.3.2 Different Types of Data Processing = 38
• 1.3.3 Bistatic and Netted Bistatic Radar Systems = 41
• 1.4 TRACKING FILTERS = 46
• 1.4.1 A View of Modern System Theory = 46
• 1.4.2 Stochastic Filtering Theory = 47
• 1.4.3 Application of Theory = 54
• 1.5 APPLICATION OF RADAR DATA-PROCESSING SYSTEMS = 57
• 1.5.1 Examples of RDP Application = 58
• 1.6 SUMMARY AND CONCLUSIONS = 62
• 1.7 REFERENCES = 63
• 2. REVIEW OF UNDERLYING-MATHEMATICAL TECHNIQUES = 65
• 2.1 INTRODUCTION TO ESTIMATION THEORY = 66
• 2.1.1 Historical Survey = 66
• 2.1.2 Basic Definitions = 66
• 2.1.3 Classification of Estimation Problems = 67
• 2.1.4 Least-Square Estimate = 68
• 2.1.5 Mean-Square Estimate = 70
• 2.1.6 Maximum-Likelihood Estimate = 71
• 2.1.7 Maximum A-Posteriori Probability(Bayes) Estimate = 72
• 2.2 DETAILED DESCRIPTION OF MEAN-SQUARE ESTIMATION FOR PARAMETRIC PROBLEMS = 74
• 2.2.1 General Solution of the MSE Problem = 74
• 2.2.2 Linear Mean-Square Estimator = 75
• 2.3 MEAN-SQUARE ESTIMATION FOR DYNAMIC PROBLEMS = 79
• 2.3.1 System Models = 79
• 2.3.2 Filtering, Prediction and Smoothing = 82
• 2.3.3 MSE Linear Prediction and Filtering = 83
• 2.4 KALMAN FILTERING = 85
• 2.4.1 Discrete-Time Kalman Filter and Predictor = 85
• 2.4.2 Numerical Example = 91
• 2.4.3 Steady-State Solution for the Kalman Filter = 94
• 2.5 ADAPTIVE FILTERING = 98
• 2.5.1 Introduction = 98
• 2.5.2 Sensitivity and Error Divergence in the Kalman Filter = 100
• 2.5.3 Bayesian Adaptive Filtering Techniques = 101
• 2.5.4 Sub-Optimal Non-Bayesian Adaptive Filters = 106
• 2.6 NONLINEAR FILTERING = 110
• 2.6.1 Introduction = 110
• 2.6.2 The Extended Kalman Filter = 113
• 2.6.3 Other Sub-Optimal Filtering Techniques = 115
• 2.7 SUMMARY AND CONCLUSIONS = 124
• 2.8 REFERENCES = 127
• 3. TRACK-WHILE-SCAN SYSTEMS = 131
• 3.1 INTRODUCTION = 131
• 3.2 OVERVIEW OF TRACK-WHILE-SCAN SYSTEMS = 134
• 3.2.1 System Organisation = 135
• 3.2.2 Clutter Map Formation and Updating = 139
• 3.3 MATHEMATICAL MODELS OF THE SENSOR AND TARGET PATH = 144
• 3.3.1 Co-Ordinate Reference Systems = 144
• 3.3.2 Radar Measurements = 153
• 3.3.3 Target Model = 161
• 3.4 TRACKING FILTERS = 165
• 3.4.1 Application of Kalman Algorithm = 165
• 3.4.2 The α,β Algorithm = 174
• 3.4.3 Extension to Two-Dimensional Target Path = 187
• 3.4.4 Adaptive Procedure for Manoeuvring Target = 193
• 3.5 PLOT-TRACK PAIRING LOGIC = 192
• 3.5.1 Correlation and Assignment Algorithm = 192
• 3.5.2 Shape and Size of Correlation Gate = 197
• 3.6 TRACK INITIATION PROCEDURE = 203
• 3.6.1 Performance of Track Initiation = 203
• 3.6.2 The Sliding-Window Method = 204
• 3.6.3 An Application Example = 211
• 3.6.4 Shape and Size of the Initiation Gates = 212
• 3.7 SUMMARY AND CONCLUSIONS = 214
• 3.8 REFERENCES = 215
• 4. TRACKING ALGORITHMS = 221
• 4.1 INTRODUCTION = 221
• 4.2 REVIEW OF THE BASIC TRACKING FILTER = 222
• 4.2.1 The Singer Approach = 222
• 4.2.2 The Semi-Markov Approach = 234
• 4.2.3 Nonlinear Filtering for Radar Measurements = 241
• 4.3 ADAPTIVE FILTERING FOR A MANOEUVRING TARGET = 243
• 4.3.1 Manoeuvre Detection Algorithms = 246
• 4.3.2 Different Means of Achieving Adaptivity = 248
• 4.4 FILTERING IN A CLUTTER ENVIRONMENT = 254
• 4.4.1 The Optimal Bayesian Approach = 256
• 4.4.2 Sub-Optimal Schemes = 260
• 4.4.3 Joint Optimisation of Signal and Data Processors = 261
• 4.5 FILTERING IN A MULTITARGET ENVIRONMENT = 264
• 4.5.1 Crossing of Two Tracks = 264
• 4.5.2 Optimal and Sub-Optimal Tracking Filters = 269
• 4.5.3 Tracking of Target Formation = 273
• 4.6 EMPLOYMENT OF RADIAL VELOCITY MEASUREMENTS = 275
• 4.6.1 Single Target in a Clear Environment = 275
• 4.6.2 Single Target in a Clutter Environment = 284
• 4.6.3 Crossing of Two Tracks = 289
• 4.6.4 Linear Processing of Radial Velocity = 290
• 4.7 ACTIVE TRACKING WITH PHASED-ARRAY RADAR = 293
• 4.7.1 Adaptive Control of Radar Data Rate = 293
• 4.7.2 Multitarget Interleaved Tracking = 295
• 4.8 BISTATIC TRACKING SYSTEMS = 302
• 4.8.1 Tracking Filter Design = 302
• 4.8.2 Comparison between Monostatic and Bistatic Radar Systems = 304
• 4.9 SUMMARY AND CONCLUSIONS = 311
• 4.10 REFERENCES = 312
• INDEX = 319