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Viser: Radar Data Processing with Applications

Radar Data Processing With Applications, 1. udgave
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Radar Data Processing With Applications Vital Source e-bog

He You, Xiu Jianjuan og Guan Xin
(2016)
John Wiley & Sons
1.699,00 kr.
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Radar Data Processing with Applications

Radar Data Processing with Applications

He You, Xiu Jianjuan og Guan Xin
(2016)
Sprog: Engelsk
John Wiley & Sons, Incorporated
1.586,00 kr.
Print on demand. Leveringstid vil være ca 2-3 uger.

Detaljer om varen

  • 1. Udgave
  • Vital Source searchable e-book (Reflowable pages)
  • Udgiver: John Wiley & Sons (August 2016)
  • Forfattere: He You, Xiu Jianjuan og Guan Xin
  • ISBN: 9781118956885
A systematic introduction to the theory, development and latest research results of radar data processing technology • Presents both classical theory and development methods of radar data processing • Provides state-of-the-art research results, including data processing for modern style radars, and tracking performance evaluation theory • Includes coverage of performance evaluation, registration algorithm for Radar network, data processing of passive radar, pulse Doppler radar, and phased array radar • Has applications for those engaged in information engineering, radar engineering, electronic countermeasures, infrared techniques, sonar techniques, and military command
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Detaljer om varen

  • Hardback: 560 sider
  • Udgiver: John Wiley & Sons, Incorporated (Oktober 2016)
  • Forfattere: He You, Xiu Jianjuan og Guan Xin
  • ISBN: 9781118956861
A systematic introduction to the theory, development and latest research results of radar data processing technology

- Presents both classical theory and development methods of radar data processing
- Provides state-of-the-art research results, including data processing for modern style radars, and tracking performance evaluation theory
- Includes coverage of performance evaluation, registration algorithm for Radar network, data processing of passive radar, pulse Doppler radar, and phased array radar
- Has applications for those engaged in information engineering, radar engineering, electronic countermeasures, infrared techniques, sonar techniques, and military command
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 0-1 Integer Programming Algorithm 126
7.4.1 Calculation of the Logarithm Likelihood Ratio 126
7.4.2 0-1 Linear Integer Programming Algorithm 128
7.4.3 Recursive 0-1 Integer Programming Algorithm 129
7.4.4 Application of 0-1 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 1
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