Remote Sensing of Earth Based Radar Objects
Autor A.I. Kozlov, L.P. Ligthart, A.I. Logvinen Limba Engleză Hardback – 12 oct 2019
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Specificații
ISBN-13: 9781402035142
ISBN-10: 1402035144
Pagini: 900
Dimensiuni: 155 x 235 mm
Ediția:1st ed. 2019
Editura: SPRINGER NETHERLANDS
Colecția Springer
Locul publicării:Dordrecht, Netherlands
ISBN-10: 1402035144
Pagini: 900
Dimensiuni: 155 x 235 mm
Ediția:1st ed. 2019
Editura: SPRINGER NETHERLANDS
Colecția Springer
Locul publicării:Dordrecht, Netherlands
Public țintă
ResearchCuprins
Preface xiv
Acknowledgements xv
PART I – INTRODUCTION
A Scope of the subject-description of the research program xvi
B Outline of the book xvii
PART II : THEORY ON REMOTE SENSING OF EARTH BASED RADAR
OBJECTS (CLASSIFICATION –RADAR CONTRAST)
Chapter 1: Classification of radar objects
Introduction 3
1.2 Traditional classification methods for radar objects 5
1.2.1 Deterministic methods 5
1.2.1.1 Decision function method 5
1.2.1.2 Distance method in the signature space 6
1.2.2 Stochastic methods 7
1.2.2.1 Bayes’ method 7
1.2.2.2 Accounting errors of experiments 9
1.3 Modified classification methods for radar objects using polarization parameters 11
1.3.1 Deterministic methods 11
1.3.1.1 Classification based on the radio-wave polarization characteristics 11
1.3.1.2 Classification based on the radar objects polarization characteristics 11
1.3.2 Stochastic methods 12
1.3.2.1 Polarization modified Bayes’ method 12
1.3.2.2 The influence of errors on the determination of the boundaries 20
1.3.2.3 The influence of PDF errors on the errors in the signature measurement 23
1.4 Application of polarization-based classification methods 26
1.4.1 Layered vegetation model 26
1.4.2 Computational results 31
1.5 Conclusions 40
Chapter 2: Inverse problem, method and analysis.
2.1 Introduction 42
2.2 Inverse scattering methods 43
2.2.1 Outline of inversion methods 45
Inversion algorithms 47
2.2.2.1 Newton method 47
2.2.2.2 Gradient method 48
2.2.2.3 Conjugate gradient method 49
2.2.2.4 Levenberg-Marquardt method 49
2.3 Example of an electromagnetic inverse scattering problem 50
2.4 Examples of inversion: experiments and simulations 56
2.4.1 Imaging of a bounded object by non-linear inversion in TE scattering 57
Imaging of single and multiple buried (underground) objects with 61
inverse scattering and SAR processing.
2.4.3 Imaging (2D-3D) of biomedical data 65
2.4.4 Depolarization effects in inverse scattering problems: an appraisal of
basic factors. 72
2.5 Summary and conclusions 73
2.5.1 Summary of inversion methods 73
2.5.2 Summary of results and conclusions 75
Chapter 3: Description of direct and interfering electromagnetic waves in
scattering problems.
3.1 Introduction 78
3.2 Main characteristics of radio wave scattering 81
3.2.1 Phenomenological models 81
3.2.2 Geometrical models 82
3.2.3 Statistical models 84
3.2.3.1 Model 1 84
3.2.3.2 Model 2 86
3.2.3.3 Model 3 88
3.3 The system of independent scatterers 90
3.3.1 General relations 90
3.3.2 Completely chaotic orientation of scatterers 93
3.3.3 Scatterers with predominant horizontal orientation 94
3.3.4 Scatterers with predominant vertical orientation 95
3.4 Classification of the forms of Earth surfaces 98
3.5 Generalized reflection characteristics of Earth surfaces 100
3.6 Polarization characteristics of Earth surfaces 108
3.6.1 Water surface 108
3.6.2 Ground surface 115
3.7 Scattering-reflection modeling: summary 122
3.7.1 Application 122
3.7.2 Verification 122
3.8 Conclusions 123
Chapter 4: Relation between electrodynamic characteristics and radar polarization
state.
4.1 Introduction 124
4.2 Smooth homogeneous medium 126
4.3 Smooth inhomogeneous medium 137
4.3.1 General relations 137
4.3.2 Exponential layer 139
4.3.3 Quadratic layer 139
4.3.4 Vertical scanning incidence 140
4.3.4.1 Polynomial layer 140
4.3.4.2 Linear layer 141
4.3.4.3 Parabolic layer 142
4.3.4.4 Matching layer 143
4.3.4.5 Intermediate layer 145
4.3.5 Equation for the scattering matrix elements 147
4.4 Rough surfaces 152
4.4.1 Scattering matrix for model 1 154
4.4.2 Scattering matrix for model 2 155
4.4.3 Scattering matrix for model 3 156
4.4.4 Scattering matrix for model 4 157
4.4.5 Statistical characteristics of the scattering matrix elements 158
Relation between eigenvalues, proper polarization basis coordinates and
complex permittivity 165
4.5.1 Scattering matrix invariants 165
4.5.1.1 Smooth homogeneous surface model 165
4.5.1.2 Smooth inhomogeneous surface model 165
4.5.1.3 Model 1 166
4.5.1.4 Model 2 166
4.5.1.5 Model 3 166
4.5.2 Eigenvalues and proper polarization basis 167
4.5.2.1 Model 1 168
4.5.2.2 Model 2 168
4.6 Conclusions 169
Chapter 5: Deterministic and stochastic modeling of objects.
5.1 Introduction 172
5.1.1 KLL sphere 173
5.2 Deterministic modeling 174
5.2.1 Main characteristics of the radar target scattering matrix elements 174
5.2.2 Modeling with use of the KLL sphere 178
5.3 Statistical modeling 188
5.3.1 Transformation of the statistical characteristics of the scattering
matrix elements. 188
5.3.1.1 Probability density function (PDF) 188
5.3.1.2 Average values and dispersion 190
5.3.2 Construction of statistical models of radar targets 194
5.3.2.1 The main principle of model synthesis 194
5.3.2.2 generalized algorithm for determination of the distribution laws 195
5.4 Summary 206
5.4.1 Applications 206
5.4.2 Verification 207
5.4.2.1 Deterministic modeling 207
5.4.2.2 Statistical modeling 207
5.5 Conclusions 207
Chapter 6: Method to increase polarization contrast of radar objects
6.1 Introduction 209
6.2 General principles of polarization discrimination of radar objects 212
6.3 Radar contrast control 215
6.4 Orthogonalization method 222
6.4.1 Effect of angle 227
6.4.1.1 Uniform distribution of angle 227
6.4.1.2 Gaussian distribution of angle 231
6.4.2 Effect of signal and interference power characteristics 234
6.5 Polarization-compensation method 238
6.6 Methods to increase the radar contrast: summary 243
6.6.1 Applications 243
6.6.2 Verification 243
6.7 Conclusions 244
Chapter 7: Accuracy and sensitivity analysis of object parameters.
7.1 Introduction 246
Application of Markov filtering for the increase of accuracy and reliability
of objects parameters determination 248
7.2.1 Problem statement 248
7.2.2 Main principles of the Markov message filtering 251
7.2.3 Markov filtering of linearly polarized radar signals 254
7.2.4 Markov filtering of an elliptically polarized radar signal 261
Experimental test of operating performance of non-linear Markov filtering
algorithm 263
7.4 Description of the equipment 272
7.5 Summary 280
7.5.1 Applications 280
7.5.2 Verification 280
7.6 Conclusions 281
Chapter 8: Requirements to the accuracy and reliability of the equipment for
Determining objects parameters and signal characteristics
8.1 Introduction 282
8.2 The main sources of measurements errors 284
8.3 The angle noise 286
The polarization algorithms for increasing the accuracy of determining
objects coordinates 287
8.5 The probabilistic characteristics of fluctuations of signal’s angles of arrival 289
8.5.1 The analysis of statistical modeling results 301
8.6 The effects of the underlying surface 303
8.7 The estimation of the polarization methods efficiency 307
Summary 310
8.8.1 Applications 310
8.8.2 Verification 310
8.9 Conclusions 311
PART III: EXPERIMENTS AND DATA-SIGNAL PROCESSING
Chapter 9: Requirements-system specifications-functional diagrams of radar
equipment for experiments allowing polarization diagnostics.
9.1 Introduction 312
9.2 Mode of complete polarization scanning 315
Main requirements for radars with varying polarization modes of emitted
electromagnetic waves 317
9.4 Radar with linear polarization modes 319
9.5 Radar with circular polarization mode 322
Radar with combined modes of polarization for study of the statistical
characteristics of the objects. 328
9.7 Radar with combined modes of polarization and with spectral analysis 333
9.8 Software for polarization parameters processing 337
9.9 Summary 339
9.9.1 Applications 339
9.9.2 Verification 340
9.10 Conclusions 340
Chapter 10: Adaptive algorithms and signal processing.
10.1 Introduction 342
10.2 Statement of the problem 344
Optimal filtering of information and concomitant (non-information) signal
parameters. 346
10.4 Application of ‘separation’ algorithm 353
10.5 Correlation relations with optimal filtering of polarized signals. 356
10.6 Summary 362
10.6.1 Application. 362
10.6.2 Verification 363
10.7 Conclusions 363
Chapter 11: Criteria for testing the radar functions. 365
Chapter 12: Methods for parameter evaluation. ~415
Chapter 13: Measurement campaigns using 1.8 cm and 3.2 cm coherent radar with ~455
controlled polarization capabilities. Part I and II.
Chapter 14: Part I: Data processing and data analysis of experiments. ~495
Part II: Refinement of theory and experiments. ~530
Chapter 15: Comparisons between theory and experiments. ~560
Chapter 16: Overview and new areas of research on modeling and verification of ~590
Earth based radar objects.
Chapter 17: Detection and classification obtained by polarimetric radars.
17.1 Introduction: Results obtained from remote sensing of the atmosphere,
precipitation, clouds, turbulence, and on earth surface, urban areas, forests. ~650
17.2 Radar remote sensing data for applications in forestry (source: 123 pages)
17.3 Cloud measurements with radar (source: 63 pages)
17.4 Doppler-polarimetric radar signal processing (source: 72 pages)
17.5 Contrast enhancement for depolarizing radar targets (source: 41 pages)
17.6 From snowflake to raindrop, Doppler radar observations and simulations of
precipitation (source: 64 pages)
17.7 Ground-based remote sensing of precipitation using a multi-polarized FM-CW
Doppler radar (source: 86 pages)
17.8 Conclusions ~745
PART IV: CONCLUSIONS
Chapter 18: Review of methods and applications of remote sensing ~750
Introduction
Results of remote sensing applications
Comparison-review of the inverse scattering methods analyzed
Areas of further developments of remote sensing
18.5 Concluding remarks
Appendices A to R. ~770
References. ~890
Acknowledgements xv
PART I – INTRODUCTION
A Scope of the subject-description of the research program xvi
B Outline of the book xvii
PART II : THEORY ON REMOTE SENSING OF EARTH BASED RADAR
OBJECTS (CLASSIFICATION –RADAR CONTRAST)
Chapter 1: Classification of radar objects
Introduction 3
1.2 Traditional classification methods for radar objects 5
1.2.1 Deterministic methods 5
1.2.1.1 Decision function method 5
1.2.1.2 Distance method in the signature space 6
1.2.2 Stochastic methods 7
1.2.2.1 Bayes’ method 7
1.2.2.2 Accounting errors of experiments 9
1.3 Modified classification methods for radar objects using polarization parameters 11
1.3.1 Deterministic methods 11
1.3.1.1 Classification based on the radio-wave polarization characteristics 11
1.3.1.2 Classification based on the radar objects polarization characteristics 11
1.3.2 Stochastic methods 12
1.3.2.1 Polarization modified Bayes’ method 12
1.3.2.2 The influence of errors on the determination of the boundaries 20
1.3.2.3 The influence of PDF errors on the errors in the signature measurement 23
1.4 Application of polarization-based classification methods 26
1.4.1 Layered vegetation model 26
1.4.2 Computational results 31
1.5 Conclusions 40
Chapter 2: Inverse problem, method and analysis.
2.1 Introduction 42
2.2 Inverse scattering methods 43
2.2.1 Outline of inversion methods 45
Inversion algorithms 47
2.2.2.1 Newton method 47
2.2.2.2 Gradient method 48
2.2.2.3 Conjugate gradient method 49
2.2.2.4 Levenberg-Marquardt method 49
2.3 Example of an electromagnetic inverse scattering problem 50
2.4 Examples of inversion: experiments and simulations 56
2.4.1 Imaging of a bounded object by non-linear inversion in TE scattering 57
Imaging of single and multiple buried (underground) objects with 61
inverse scattering and SAR processing.
2.4.3 Imaging (2D-3D) of biomedical data 65
2.4.4 Depolarization effects in inverse scattering problems: an appraisal of
basic factors. 72
2.5 Summary and conclusions 73
2.5.1 Summary of inversion methods 73
2.5.2 Summary of results and conclusions 75
Chapter 3: Description of direct and interfering electromagnetic waves in
scattering problems.
3.1 Introduction 78
3.2 Main characteristics of radio wave scattering 81
3.2.1 Phenomenological models 81
3.2.2 Geometrical models 82
3.2.3 Statistical models 84
3.2.3.1 Model 1 84
3.2.3.2 Model 2 86
3.2.3.3 Model 3 88
3.3 The system of independent scatterers 90
3.3.1 General relations 90
3.3.2 Completely chaotic orientation of scatterers 93
3.3.3 Scatterers with predominant horizontal orientation 94
3.3.4 Scatterers with predominant vertical orientation 95
3.4 Classification of the forms of Earth surfaces 98
3.5 Generalized reflection characteristics of Earth surfaces 100
3.6 Polarization characteristics of Earth surfaces 108
3.6.1 Water surface 108
3.6.2 Ground surface 115
3.7 Scattering-reflection modeling: summary 122
3.7.1 Application 122
3.7.2 Verification 122
3.8 Conclusions 123
Chapter 4: Relation between electrodynamic characteristics and radar polarization
state.
4.1 Introduction 124
4.2 Smooth homogeneous medium 126
4.3 Smooth inhomogeneous medium 137
4.3.1 General relations 137
4.3.2 Exponential layer 139
4.3.3 Quadratic layer 139
4.3.4 Vertical scanning incidence 140
4.3.4.1 Polynomial layer 140
4.3.4.2 Linear layer 141
4.3.4.3 Parabolic layer 142
4.3.4.4 Matching layer 143
4.3.4.5 Intermediate layer 145
4.3.5 Equation for the scattering matrix elements 147
4.4 Rough surfaces 152
4.4.1 Scattering matrix for model 1 154
4.4.2 Scattering matrix for model 2 155
4.4.3 Scattering matrix for model 3 156
4.4.4 Scattering matrix for model 4 157
4.4.5 Statistical characteristics of the scattering matrix elements 158
Relation between eigenvalues, proper polarization basis coordinates and
complex permittivity 165
4.5.1 Scattering matrix invariants 165
4.5.1.1 Smooth homogeneous surface model 165
4.5.1.2 Smooth inhomogeneous surface model 165
4.5.1.3 Model 1 166
4.5.1.4 Model 2 166
4.5.1.5 Model 3 166
4.5.2 Eigenvalues and proper polarization basis 167
4.5.2.1 Model 1 168
4.5.2.2 Model 2 168
4.6 Conclusions 169
Chapter 5: Deterministic and stochastic modeling of objects.
5.1 Introduction 172
5.1.1 KLL sphere 173
5.2 Deterministic modeling 174
5.2.1 Main characteristics of the radar target scattering matrix elements 174
5.2.2 Modeling with use of the KLL sphere 178
5.3 Statistical modeling 188
5.3.1 Transformation of the statistical characteristics of the scattering
matrix elements. 188
5.3.1.1 Probability density function (PDF) 188
5.3.1.2 Average values and dispersion 190
5.3.2 Construction of statistical models of radar targets 194
5.3.2.1 The main principle of model synthesis 194
5.3.2.2 generalized algorithm for determination of the distribution laws 195
5.4 Summary 206
5.4.1 Applications 206
5.4.2 Verification 207
5.4.2.1 Deterministic modeling 207
5.4.2.2 Statistical modeling 207
5.5 Conclusions 207
Chapter 6: Method to increase polarization contrast of radar objects
6.1 Introduction 209
6.2 General principles of polarization discrimination of radar objects 212
6.3 Radar contrast control 215
6.4 Orthogonalization method 222
6.4.1 Effect of angle 227
6.4.1.1 Uniform distribution of angle 227
6.4.1.2 Gaussian distribution of angle 231
6.4.2 Effect of signal and interference power characteristics 234
6.5 Polarization-compensation method 238
6.6 Methods to increase the radar contrast: summary 243
6.6.1 Applications 243
6.6.2 Verification 243
6.7 Conclusions 244
Chapter 7: Accuracy and sensitivity analysis of object parameters.
7.1 Introduction 246
Application of Markov filtering for the increase of accuracy and reliability
of objects parameters determination 248
7.2.1 Problem statement 248
7.2.2 Main principles of the Markov message filtering 251
7.2.3 Markov filtering of linearly polarized radar signals 254
7.2.4 Markov filtering of an elliptically polarized radar signal 261
Experimental test of operating performance of non-linear Markov filtering
algorithm 263
7.4 Description of the equipment 272
7.5 Summary 280
7.5.1 Applications 280
7.5.2 Verification 280
7.6 Conclusions 281
Chapter 8: Requirements to the accuracy and reliability of the equipment for
Determining objects parameters and signal characteristics
8.1 Introduction 282
8.2 The main sources of measurements errors 284
8.3 The angle noise 286
The polarization algorithms for increasing the accuracy of determining
objects coordinates 287
8.5 The probabilistic characteristics of fluctuations of signal’s angles of arrival 289
8.5.1 The analysis of statistical modeling results 301
8.6 The effects of the underlying surface 303
8.7 The estimation of the polarization methods efficiency 307
Summary 310
8.8.1 Applications 310
8.8.2 Verification 310
8.9 Conclusions 311
PART III: EXPERIMENTS AND DATA-SIGNAL PROCESSING
Chapter 9: Requirements-system specifications-functional diagrams of radar
equipment for experiments allowing polarization diagnostics.
9.1 Introduction 312
9.2 Mode of complete polarization scanning 315
Main requirements for radars with varying polarization modes of emitted
electromagnetic waves 317
9.4 Radar with linear polarization modes 319
9.5 Radar with circular polarization mode 322
Radar with combined modes of polarization for study of the statistical
characteristics of the objects. 328
9.7 Radar with combined modes of polarization and with spectral analysis 333
9.8 Software for polarization parameters processing 337
9.9 Summary 339
9.9.1 Applications 339
9.9.2 Verification 340
9.10 Conclusions 340
Chapter 10: Adaptive algorithms and signal processing.
10.1 Introduction 342
10.2 Statement of the problem 344
Optimal filtering of information and concomitant (non-information) signal
parameters. 346
10.4 Application of ‘separation’ algorithm 353
10.5 Correlation relations with optimal filtering of polarized signals. 356
10.6 Summary 362
10.6.1 Application. 362
10.6.2 Verification 363
10.7 Conclusions 363
Chapter 11: Criteria for testing the radar functions. 365
Chapter 12: Methods for parameter evaluation. ~415
Chapter 13: Measurement campaigns using 1.8 cm and 3.2 cm coherent radar with ~455
controlled polarization capabilities. Part I and II.
Chapter 14: Part I: Data processing and data analysis of experiments. ~495
Part II: Refinement of theory and experiments. ~530
Chapter 15: Comparisons between theory and experiments. ~560
Chapter 16: Overview and new areas of research on modeling and verification of ~590
Earth based radar objects.
Chapter 17: Detection and classification obtained by polarimetric radars.
17.1 Introduction: Results obtained from remote sensing of the atmosphere,
precipitation, clouds, turbulence, and on earth surface, urban areas, forests. ~650
17.2 Radar remote sensing data for applications in forestry (source: 123 pages)
17.3 Cloud measurements with radar (source: 63 pages)
17.4 Doppler-polarimetric radar signal processing (source: 72 pages)
17.5 Contrast enhancement for depolarizing radar targets (source: 41 pages)
17.6 From snowflake to raindrop, Doppler radar observations and simulations of
precipitation (source: 64 pages)
17.7 Ground-based remote sensing of precipitation using a multi-polarized FM-CW
Doppler radar (source: 86 pages)
17.8 Conclusions ~745
PART IV: CONCLUSIONS
Chapter 18: Review of methods and applications of remote sensing ~750
Introduction
Results of remote sensing applications
Comparison-review of the inverse scattering methods analyzed
Areas of further developments of remote sensing
18.5 Concluding remarks
Appendices A to R. ~770
References. ~890
Caracteristici
Represents a significant contribution and a fusion of scientific research and knowledge on polarimetric radar availbale from Russia, Western and Eastern sorces
Includes advanced mathematical methods for solving inverse problems applied to polarimetric radar
Includes advanced mathematical methods for solving inverse problems applied to polarimetric radar
Descriere
Here is a complete review of the theory and practice of remote radio sensing applied to detection and classification problems with (polarimetric) radar in microwave scattering propagation channel. Covers signal processing, modeling, classification and more.