Taking an innovative look at Synthetic Aperture Radar (SAR), this practical reference fully covers new developments in SAR and its various methodologies and enables readers to interpret SAR imagery

An essential reference on polarimetric Synthetic Aperture Radar (SAR), this book uses scattering theory and radiative transfer theory as a basis for its treatment of topics. It is organized to include theoretical scattering models and SAR data analysis techniques, and presents cutting-edge research on theoretical modelling of terrain surface. The book includes quantitative approaches for remote sensing, such as the analysis of the Mueller matrix solution of random media, mono-static and bistatic SAR image simulation. It also covers new parameters for unsupervised surface classification, DEM inversion, change detection from multi-temporal SAR images, reconstruction of building objects from multi-aspect SAR images, and polarimetric pulse echoes from multi-layering scatter media.

Structured to encourage methodical learning, earlier chapters cover core material, whilst later sections involve more advanced new topics which are important for researchers. The final chapter completes the book as a reference by covering SAR interferometry, a core topic in the remote sensing community.

• Features theoretical scattering models and SAR data analysis techniques
• Explains the simulation of SAR images for mono- and bi-static radars, covering both qualitative and quantitative information retrieval
• Chapter topics include: theoretical scattering models; SAR data analysis and processing techniques; and theoretical quantitative simulation reconstruction and inversion techniques
• Structured to enable both academic learning and independent study, laying down the foundations first of all before advancing to more complex topics
• Experienced author team presents mathematical derivations and figures so that they are easy for readers to understand
• Pitched at graduate-level students in electrical engineering, physics, earth and space sciences, as well as researchers
• MATLAB code available for readers to run their own routines

An invaluable reference for research scientists, engineers and scientists working on polarimetric SAR hardware and software, Application developers of SAR and polarimetric SAR, remote sensing specialists working with SAR data - using ESA.

Ya-Qiu Jin, Fudan University, China
Professor Jin is Chair Professor and Director of the Key Lab of Wave Scattering and Remote Sensing Information, at Fudan University, Shanghai, China. He is an IEEE Fellow, a Fellow of the Electromagnetics Academy (USA) and CIE as well as being Chair of the IEEE Fellow Evaluation Committee (GRSS), a Member of IEEE GRSS AdCom, and Associate Editor of IEEE Transactions on Geoscience and Remote Sensing.

Feng Xu, Intelligent Automation, Inc, USA
Dr. Xu holds the post of Research Scientist at Intelligent Automation, Inc, Rockville, USA. He took his PhD at Fudan University in Shanghai, China and was a postdoctoral researcher at NOAA/NESDIS, USA, from 2008-2009.

Preface xi

1 Basics of Polarimetric Scattering 1

1.1 Polarized Electromagnetic Wave 1

1.1.1 Jones Vector and Scattering Matrix 1

1.1.2 Stokes Vector and Mueller Matrix 4

1.2 Volumetric Scattering 9

1.2.1 Small Particle under Rayleigh-Gans Approximation 9

1.2.2 Slim Cylinder 11

1.3 Surface Scattering 13

1.3.1 Plane Surface 13

1.3.2 Rough Surface 14

1.3.3 Kirchhoff Approximation 16

1.3.4 Small-Perturbation Approximation 19

1.3.5 Two-Scale Approximation 21

1.3.6 Integral Equation Method 22

1.3.7 Tilted Surface or Oriented Object 25

References 26

2 Vector Radiative Transfer 29

2.1 Radiative Transfer Equation 29

2.1.1 Specific Intensity and Stokes Vector 29

2.1.2 Thermal Emission and Brightness Temperature 32

2.1.3 Vector Radiative Transfer Equation 33

2.2 Components in Radiative Transfer Equation 35

2.2.1 Scattering, Absorption, and Extinction Coefficients 35

2.2.2 Extinction Matrix 36

2.2.3 Phase Matrix 39

2.3 Mueller Matrix Solution 40

2.3.1 First-Order Mueller Matrix Solution 40

2.3.2 Modeling of Vegetation Canopy over Rough Surface 43

2.3.3 Numerical Examples of Modeling of Vegetation Canopy 47

2.4 Polarization Indices and Entropy 52

2.4.1 Eigen-Analysis of Mueller Matrix 52

2.4.2 Relationship between Eigenvalues, Entropy, and Polarization Indices 53

2.4.3 Demonstration with AirSAR Imagery 55

2.5 Statistics of Stokes Parameters 59

2.5.1 Multi-Look Covariance Matrix and Complex Wishart Distribution 59

2.5.2 PDFs of the Four Stokes Parameters 60

2.5.3 Comparison with AirSAR Image Data 67

Appendix 2A: Phase Matrix of Non-Spherical Particles 72

References 76

3 Imaging Simulation of Polarimetric SAR: Mapping and Projection Algorithm 79

3.1 Fundamentals of SAR Imaging 79

3.1.1 Ranging and Pulse Compression 79

3.1.2 Synthetic Aperture and Azimuth Focusing 82

3.1.3 SAR Imaging Algorithm 85

3.2 Mapping and Projection Algorithm 90

3.2.1 Mapping and Projection 91

3.2.2 Mapping and Projection Algorithm for Fast Computation 95

3.2.3 Scattering Models for Terrain Objects 101

3.2.4 Speckle Model and Raw Data Generation 105

3.3 Platform for SAR Simulation 108

3.3.1 Simulation of Individual Terrain Objects 108

3.3.2 Simulation of Comprehensive Terrain Scene 112

3.3.3 Extensions 119

References 121

4 Bistatic SAR: Simulation, Processing, and Interpretation 123

4.1 Bistatic Mapping and Projection Algorithm (BI-MPA) 124

4.1.1 Configurations of BISAR 124

4.1.2 Three-Dimensional Projection and Mapping 125

4.1.3 Multiple Scattering Terms 130

4.2 Scattering Models and Signal Model 130

4.2.1 Models of Terrain Objects 130

4.2.2 Raw Signal Model for BISAR 131

4.3 Simulated BISAR Images 136

4.4 Polarimetric Characteristics of BISAR Image 141

4.5 Unified Bistatic Polarization Bases 146

4.6 Raw Signal Processing of Stripmap BISAR 150

4.6.1 Approximate Form of the Point Target Response 150

4.6.2 Validity Condition and an Iterative Solution 155

4.6.3 Extension of Range Doppler Method 157

4.6.4 Simulation and Discussion 159

References 164

5 Radar Polarimetry and Deorientation Theory 167

5.1 Radar Polarimetry and Target Decomposition 167

5.1.1 Polarization Transformation 167

5.1.2 Radar Polarimetry 173

5.1.3 Target Decomposition 180

5.2 Deorientation Theory 184

5.2.1 Deorientation 184

5.2.2 Efficacy of Deorientation 192

5.3 Terrain Surface Classification 198

5.3.1 Terrain Scattering Modeling and Classification Spectrum 198

5.3.2 Application to SIR-C Data 201

5.3.3 Orientation Analysis 206

Appendix 5A: Matrix Transformations under Various Conventions 207

5a.1 Transformation under Wave Coordinates (FSA) 209

5a.2 Transformation under Antenna Coordinates (BSA) 211

5a.3 Interconversion between Wave Coordinates (FSA) and Antenna Coordinates (BSA) 213

References 213

6 Inversions from Polarimetric SAR Images 215

6.1 Inversion of Digital Elevation Mapping 216

6.1.1 The Shift of Orientation Angle 216

6.1.2 Range and Azimuth Angles from Euler Angle Transformation 218

6.1.3 The Azimuth Angle of Every Pixel in a SAR Image 220

6.2 An Example of Algorithm Implementation 221

6.3 Inversion…