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E-raamat: Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach

(Chinese Academy of Sciences, Beijing, China)
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Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach demonstrates the use of image simulation for SAR. It covers the various applications of SAR (including feature extraction, target classification, and change detection), provides a complete understanding of SAR principles, and illustrates the complete chain of a SAR operation.

The book places special emphasis on a ground-based SAR, but also explains space and air-borne systems. It contains chapters on signal speckle, radar-signal models, sensor-trajectory models, SAR-image focusing, platform-motion compensation, and microwave-scattering from random media.

While discussing SAR image focusing and motion compensation, it presents processing algorithms and applications that feature extraction, target classification, and change detection. It also provides samples of simulation on various scenarios, and includes simulation flowcharts and results that are detailed throughout the book.

Introducing SAR imaging from a systems point of view, the author:











Considers the recent development of MIMO SAR technology Includes selected GPU implementation Provides a numerical analysis of system parameters (including platforms, sensor, and image focusing, and their influence) Explores wave-target interactions, signal transmission and reception, image formation, motion compensation Covers all platform motion compensation and error analysis, and their impact on final image radiometric and geometric quality Describes a ground-based SFMCW system

Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach is dedicated to the use, study, and development of SAR systems. The book focuses on image formation or focusing, treats platform motion and image focusing, and is suitable for students, radar engineers, and microwave remote sensing researchers.

Arvustused

"This book provides readers with a comprehensive and complete description of synthetic aperture radar principle. Its unique feature of full-blown SAR image simulations and modeling, including sensor and target location, targets geometric and radiometric scattering characteristics, and clutters from system and environment, distinguishes this book from other SAR processing books. Insightful and state of arts information on SAR trajectory, SAR focusing and motion compensation are clearly detailed. For the first time, satellite SAR systems, such as RadarSAT-2, TerraSAR-X and ALOS/PALSAR and their imaging configurations, are integrated into the simulation and modeling. One of the highlights of this book rests at image simulations of hard targets, such as B757-200, B747-400, A321 and MD80 for various aspect angles. These simulations make target identification possible as illustrated using real TerraSAR-X SAR images. This book can be used both as a reference book for SAR researchers and as a textbook for graduate students if exercises can be supplemented." Jon-Sen Lee, Naval Research Laboratory (Retired), Washington DC, USA

"The book is based on professor Kun-Shan Chens vast experience, both theoretical and practical, over the last three decades. It covers topics in SAR systems which are relevant for senior undergraduate students, graduate students, engineers and researchers. The algorithms for motion compensation and image formation; and demonstration of applications of these are particularly useful." Professor Academician Dr. Hean-Teik Chuah, FIEEE, President of Universiti Tunku Abdul Rahman, Malaysia

"No book of this scope and depth comes about casually, and this book is no exception. The book is sharply focused and seems remarkably free of typos, which is testimony of the care and attention given by the author and the editors. Principles of Synthetic Aperture Radar Imaging: A Systems Simulation Approach has been faithful to its ti

Preface xi
Acknowledgments xiii
Author xv
Chapter 1 Preliminary Background
1(18)
1.1 Signals and Linear System
1(4)
1.1.1 Analytic Signal
3(2)
1.2 Basics of Radar Signal
5(7)
1.2.1 Single Pulse
5(1)
1.2.2 Pulse Train
6(1)
1.2.3 Frequency-Modulated Continuous Wave
7(5)
1.3 Concept of Synthetic Aperture Radar
12(7)
Appendix Useful Fourier Transform Pairs and Properties
15(2)
References
17(2)
Chapter 2 SAR Models
19(32)
2.1 Introduction
19(1)
2.2 Physical Model
19(18)
2.2.1 Radar Scattering Power and Scattering Coefficient
20(4)
2.2.2 Antenna Illuminated Area
24(1)
2.2.3 Scattering Effects
24(2)
2.2.4 Radar Speckles
26(11)
2.3 Target RCS Models
37(7)
2.3.1 Deterministic Target
37(3)
2.3.2 Distributed Target
40(1)
2.3.2.1 Single Scattering
40(2)
2.3.2.2 Double Scattering
42(2)
2.4 System Model
44(7)
2.4.1 Slant Range Projection
44(1)
2.4.2 Point Target Model
44(2)
Appendix Derivation of Multilook Amplitude Distribution
46(2)
References
48(3)
Chapter 3 SAR Data and Signal
51(16)
3.1 Introduction
51(1)
3.2 Chirp Signal
51(7)
3.2.1 Echo Signal in Two Dimensions
51(3)
3.2.2 Demodulated Echo Signal
54(1)
3.2.3 Range Cell Migration
55(3)
3.3 Properties of Doppler Frequency
58(4)
3.3.1 Squint Effects
58(1)
3.3.2 FM Signal Aliasing
58(2)
3.3.3 Platform Velocity
60(2)
3.4 FM Continuous Wave
62(5)
3.4.1 Signal Parameters
62(2)
3.4.2 Object to Data Mapping
64(1)
References
65(2)
Chapter 4 SAR Path Trajectory
67(24)
4.1 Introduction
67(1)
4.2 Time Coordinate System
67(2)
4.3 Spatial Coordinate System
69(5)
4.3.1 Orbital Parameters
69(1)
4.3.2 Geocentric and Geodetic Systems and Their Transformation
70(2)
4.3.3 Conversion between ECR and ECI Coordinates
72(2)
4.4 Satellite Position, Velocity, and Their Estimations
74(6)
4.4.1 Orbital State Vector
75(2)
4.4.2 Radar Beam-Pointing Vector
77(1)
4.4.3 Target Position on Earth
78(2)
4.5 Coordinates for Aircraft Platform
80(11)
4.5.1 ENU and NED Coordinates
81(1)
4.5.2 RPY Coordinate and Flight Path Angle
82(1)
4.5.3 Simulation Example
83(5)
References
88(3)
Chapter 5 SAR Image Focusing
91(28)
5.1 Introduction
91(1)
5.2 Generic Range-Doppler Algorithm
91(13)
5.2.1 Range Cell Migration Correction
95(3)
5.2.2 Doppler Centroid Estimation
98(1)
5.2.3 Doppler Rate Estimation
98(6)
5.3 Chirp Scaling Algorithm
104(15)
5.3.1 Range Cell Migration
105(2)
5.3.2 Chirp Scaling Functions
107(3)
5.3.3 Numerical Examples
110(3)
Appendix Stationary Phase Approximation
113(3)
References
116(3)
Chapter 6 Motion Compensation
119(22)
6.1 Introduction
119(1)
6.2 Parameters and Their Conversions
120(7)
6.2.1 Airborne System
120(2)
6.2.2 Spaceborne System
122(5)
6.3 Signal Model for Motion Compensation
127(2)
6.4 Numerical Simulation
129(12)
References
137(4)
Chapter 7 Stationary FMCW SAR
141(32)
7.1 Introduction
141(1)
7.2 SFMCW Signal Model
141(4)
7.3 Image Focusing of SFMCW System
145(8)
7.3.1 Focusing by RDA
145(2)
7.3.2 Focusing by CSA
147(6)
7.4 Motion Compensation
153(9)
7.5 Experimental Measurements
162(11)
7.5.1 Measurement Setup
162(1)
7.5.2 Image Focusing
163(8)
References
171(2)
Chapter 8 System Simulations and Applications
173(26)
8.1 Introduction
173(1)
8.2 Simulation Demonstration
173(5)
8.2.1 Point Target Response
173(2)
8.2.2 Target Location
175(3)
8.3 Computation Complexity
178(3)
8.4 Contrast Enhancement by Nonquadratic Optimization
181(10)
8.4.1 Algorithm for Stripmap Mode SAR by Nonquadratic Regularization
183(2)
8.4.2 Performance Check
185(6)
8.5 Feature Vectors and Extraction
191(2)
8.6 Applications to Target Identification
193(6)
8.6.1 Test-Simulated SAR Images
193(1)
8.6.2 Test on Real SAR Images
194(3)
References
197(2)
Index 199
Kun-Shan Chen received a PhD degree in electrical engineering from the University of Texas at Arlington in 1990. From 1992 to 2014, he was with the faculty of National Central University, Taiwan. He joined the Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, in 2014, and has served the Department of Electrical Engineering, The University of Texas at Arlington, USA, as a research professor since 2014. He has authored or coauthored over 120 journal papers, contributed seven book chapters, is a coauthor of one book, and a fellow of The Institute of Electrical and Electronics Engineers (IEEE).
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