Inverse synthetic aperture radar imaging with MATLAB algorithms

Build your knowledge of SAR/ISAR imaging with this comprehensive and insightful resource The newly revised Second Edition of Inverse Synthetic Aperture Radar Imaging with MATLAB Algorithms covers in greater detail the fundamental and advanced topics necessary for a complete understanding of inverse...

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Main Author Ozdemir, Caner
Format eBook Book
LanguageEnglish
Published Hoboken John Wiley & Sons, Inc 2021
Wiley
John Wiley & Sons, Incorporated
Wiley-Blackwell
Edition2
SeriesWiley Series in Microwave and Optical Engineering
Subjects
MATLAB
Signal processing
Synthetic aperture radar
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Abstract Build your knowledge of SAR/ISAR imaging with this comprehensive and insightful resource The newly revised Second Edition of Inverse Synthetic Aperture Radar Imaging with MATLAB Algorithms covers in greater detail the fundamental and advanced topics necessary for a complete understanding of inverse synthetic aperture radar (ISAR) imaging and its concepts. Distinguished author and academician, Caner Özdemir, describes the practical aspects of ISAR imaging and presents illustrative examples of the radar signal processing algorithms used for ISAR imaging. The topics in each chapter are supplemented with MATLAB codes to assist readers in better understanding each of the principles discussed within the book. This new edition incudes discussions of the most up-to-date topics to arise in the field of ISAR imaging and ISAR hardware design. The book provides a comprehensive analysis of advanced techniques like Fourier-based radar imaging algorithms, and motion compensation techniques along with radar fundamentals for readers new to the subject. The author covers a wide variety of topics, including: * Radar fundamentals, including concepts like radar cross section, maximum detectable range, frequency modulated continuous wave, and doppler frequency and pulsed radar * The theoretical and practical aspects of signal processing algorithms used in ISAR imaging * The numeric implementation of all necessary algorithms in MATLAB * ISAR hardware, emerging topics on SAR/ISAR focusing algorithms such as bistatic ISAR imaging, polarimetric ISAR imaging, and near-field ISAR imaging, * Applications of SAR/ISAR imaging techniques to other radar imaging problems such as thru-the-wall radar imaging and ground-penetrating radar imaging Perfect for graduate students in the fields of electrical and electronics engineering, electromagnetism, imaging radar, and physics, Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms also belongs on the bookshelves of practicing researchers in the related areas looking for a useful resource to assist them in their day-to-day professional work.
AbstractList This book is an updated edition covering in greater detail the fundamentals of inverse synthetic aperture radar (ISAR). Theoretical as well as practical aspects of ISAR are presented and illustrative examples are used to describe the signal processing algorithms used for ISAR imaging. The topics presented in each chapter are supported by MATLAB codes to assist the users in better understanding the ISAR imaging principles. This edition includes discussions of new topics related to ISAR imaging and describes hardware design for ISAR.
Build your knowledge of SAR/ISAR imaging with this comprehensive and insightful resource   The newly revised Second Edition of Inverse Synthetic Aperture Radar Imaging with MATLAB Algorithms covers in greater detail the fundamental and advanced topics necessary for a complete understanding of inverse synthetic aperture radar (ISAR) imaging and its concepts. Distinguished author and academician, Caner Özdemir, describes the practical aspects of ISAR imaging and presents illustrative examples of the radar signal processing algorithms used for ISAR imaging. The topics in each chapter are supplemented with MATLAB codes to assist readers in better understanding each of the principles discussed within the book.   This new edition incudes discussions of the most up-to-date topics to arise in the field of ISAR imaging and ISAR hardware design. The book provides a comprehensive analysis of  advanced techniques like Fourier-based  radar imaging algorithms, and motion compensation techniques along with radar fundamentals for readers new to the subject.  The author covers a wide variety of topics, including:  Radar fundamentals, including concepts like radar cross section, maximum detectable range, frequency modulated continuous wave, and doppler frequency and pulsed radar  The theoretical and practical aspects of signal processing algorithms used in ISAR imaging  The numeric implementation of all necessary algorithms in MATLAB  ISAR hardware, emerging topics on SAR/ISAR focusing algorithms such as bistatic ISAR imaging, polarimetric ISAR imaging, and near-field ISAR imaging,   Applications of SAR/ISAR imaging techniques to other radar imaging problems such as thru-the-wall radar imaging and ground-penetrating radar imaging   Perfect for graduate students in the fields of electrical and electronics engineering, electromagnetism, imaging radar, and physics, Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms also belongs on the bookshelves of practicing researchers in the related areas looking for a useful resource to assist them in their day-to-day professional work. 
Build your knowledge of SAR/ISAR imaging with this comprehensive and insightful resource The newly revised Second Edition of Inverse Synthetic Aperture Radar Imaging with MATLAB Algorithms covers in greater detail the fundamental and advanced topics necessary for a complete understanding of inverse synthetic aperture radar (ISAR) imaging and its concepts. Distinguished author and academician, Caner Özdemir, describes the practical aspects of ISAR imaging and presents illustrative examples of the radar signal processing algorithms used for ISAR imaging. The topics in each chapter are supplemented with MATLAB codes to assist readers in better understanding each of the principles discussed within the book. This new edition incudes discussions of the most up-to-date topics to arise in the field of ISAR imaging and ISAR hardware design. The book provides a comprehensive analysis of advanced techniques like Fourier-based radar imaging algorithms, and motion compensation techniques along with radar fundamentals for readers new to the subject. The author covers a wide variety of topics, including: * Radar fundamentals, including concepts like radar cross section, maximum detectable range, frequency modulated continuous wave, and doppler frequency and pulsed radar * The theoretical and practical aspects of signal processing algorithms used in ISAR imaging * The numeric implementation of all necessary algorithms in MATLAB * ISAR hardware, emerging topics on SAR/ISAR focusing algorithms such as bistatic ISAR imaging, polarimetric ISAR imaging, and near-field ISAR imaging, * Applications of SAR/ISAR imaging techniques to other radar imaging problems such as thru-the-wall radar imaging and ground-penetrating radar imaging Perfect for graduate students in the fields of electrical and electronics engineering, electromagnetism, imaging radar, and physics, Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms also belongs on the bookshelves of practicing researchers in the related areas looking for a useful resource to assist them in their day-to-day professional work.
Author Özdemir, Caner
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Snippet Build your knowledge of SAR/ISAR imaging with this comprehensive and insightful resource The newly revised Second Edition of Inverse Synthetic Aperture Radar...
This book is an updated edition covering in greater detail the fundamentals of inverse synthetic aperture radar (ISAR). Theoretical as well as practical...
Build your knowledge of SAR/ISAR imaging with this comprehensive and insightful resource   The newly revised Second Edition of Inverse Synthetic Aperture Radar...
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SubjectTerms MATLAB
Signal processing
Synthetic aperture radar
TableOfContents 3.3 Resolutions in SAR -- 3.4 SAR Image Formation -- 3.5 Range Compression -- 3.5.1 Matched Filter -- 3.5.1.1 Computing Matched Filter Output via Fourier Processing -- 3.5.1.2 Example for Matched Filtering -- 3.5.2 Ambiguity Function -- 3.5.2.1 Relation to Matched Filter -- 3.5.2.2 Ideal Ambiguity Function -- 3.5.2.3 Rectangular-Pulse Ambiguity Function -- 3.5.2.4 LFM-Pulse Ambiguity Function -- 3.5.3 Pulse Compression -- 3.5.3.1 Detailed Processing of Pulse Compression -- 3.5.3.2 Bandwidth, Resolution, and Compression Issues for LFM Signal -- 3.5.3.3 Pulse Compression Example -- 3.6 Azimuth Compression -- 3.6.1 Processing in Azimuth -- 3.6.2 Azimuth Resolution -- 3.6.3 Relation to ISAR -- 3.7 SAR Imaging -- 3.8 SAR Focusing Algorithms -- 3.8.1 RDA -- 3.8.1.1 Range Compression in RDA -- 3.8.1.2 Azimuth Fourier Transform -- 3.8.1.3 Range Cell Migration Correction -- 3.8.1.4 Azimuth Compression -- 3.8.1.5 Simulated SAR Imaging Example -- 3.8.1.6 Drawbacks of RDA -- 3.8.2 Chirp Scaling Algorithm -- 3.8.3 The ω-kA -- 3.8.4 Back-Projection Algorithm -- 3.9 Example of a Real SAR Imagery -- 3.10 Problems in SAR Imaging -- 3.10.1 Range Migration and Range Walk -- 3.10.2 Motion Errors -- 3.10.3 Speckle Noise -- 3.11 Advanced Topics in SAR -- 3.11.1 SAR Interferometry -- 3.11.2 SAR Polarimetry -- 3.12 Matlab Codes -- References -- Chapter 4 Inverse Synthetic Aperture Radar Imaging and Its Basic Concepts -- 4.1 SAR versus ISAR -- 4.2 The Relation of Scattered Field to the Image Function in ISAR -- 4.3 One-Dimensional (1D) Range Profile -- 4.4 1D Cross-Range Profile -- 4.5 Two-Dimensional (2D) ISAR Image Formation (Small Bandwidth, Small Angle) -- 4.5.1 Resolutions in ISAR -- 4.5.1.1 Range Resolution -- 4.5.1.2 Cross-Range Resolution: -- 4.5.2 Range and Cross-Range Extends -- 4.5.3 Imaging Multibounces in ISAR -- 4.5.4 Sample Design Procedure for ISAR
Cover -- Title Page -- Copyright Page -- Contents -- Preface to the Second Edition -- Acknowledgments -- Acronyms -- Chapter 1 Basics of Fourier Analysis -- 1.1 Forward and Inverse Fourier Transform -- 1.1.1 Brief History of FT -- 1.1.2 Forward FT Operation -- 1.1.3 IFT -- 1.2 FT Rules and Pairs -- 1.2.1 Linearity -- 1.2.2 Time Shifting -- 1.2.3 Frequency Shifting -- 1.2.4 Scaling -- 1.2.5 Duality -- 1.2.6 Time Reversal -- 1.2.7 Conjugation -- 1.2.8 Multiplication -- 1.2.9 Convolution -- 1.2.10 Modulation -- 1.2.11 Derivation and Integration -- 1.2.12 Parseval's Relationship -- 1.3 Time-Frequency Representation of a Signal -- 1.3.1 Signal in the Time Domain -- 1.3.2 Signal in the Frequency Domain -- 1.3.3 Signal in the Joint Time-Frequency (JTF) Plane -- 1.4 Convolution and Multiplication Using FT -- 1.5 Filtering/Windowing -- 1.6 Data Sampling -- 1.7 DFT and FFT -- 1.7.1 DFT -- 1.7.2 FFT -- 1.7.3 Bandwidth and Resolutions -- 1.8 Aliasing -- 1.9 Importance of FT in Radar Imaging -- 1.10 Effect of Aliasing in Radar Imaging -- 1.11 Matlab Codes -- References -- Chapter 2 Radar Fundamentals -- 2.1 Electromagnetic Scattering -- 2.2 Scattering from PECs -- 2.3 Radar Cross Section -- 2.3.1 Definition of RCS -- 2.3.2 RCS of Simple-Shaped Objects -- 2.3.3 RCS of Complex-Shaped Objects -- 2.4 Radar Range Equation -- 2.4.1 Bistatic Case -- 2.4.2 Monostatic Case -- 2.5 Range of Radar Detection -- 2.5.1 Signal-to-Noise Ratio -- 2.6 Radar Waveforms -- 2.6.1 Continuous Wave -- 2.6.2 Frequency-Modulated Continuous Wave -- 2.6.3 Stepped-Frequency Continuous Wave -- 2.6.4 Short Pulse -- 2.6.5 Chirp (LFM) Pulse -- 2.7 Pulsed Radar -- 2.7.1 Pulse Repetition Frequency -- 2.7.2 Maximum Range and Range Ambiguity -- 2.7.3 Doppler Frequency -- 2.8 Matlab Codes -- References -- Chapter 3 Synthetic Aperture Radar -- 3.1 SAR Modes -- 3.2 SAR System Design
Chapter 11 Near-Field ISAR Imaging
9.2.2 Bistatic ISAR Imaging Algorithm for a Target -- 9.3 Resolutions in Bistatic ISAR -- 9.3.1 Range Resolution -- 9.3.2 Cross-Range Resolution -- 9.3.3 Range and Cross-Range Extends -- 9.4 Design Procedure for Bi-ISAR Imaging -- 9.5 Bi-Isar Imaging Examples -- 9.5.1 Bi-ISAR Design Example #1 -- 9.5.2 Bi-ISAR Design Example #2 -- 9.6 Mu-ISAR Imaging -- 9.6.1 Challenges in Mu-ISAR Imaging -- 9.6.2 Mu-ISAR Imaging Example -- 9.7 Matlab Codes -- References -- Chapter 10 Polarimetric ISAR Imaging -- 10.1 Polarization of an Electromagnetic Wave -- 10.1.1 Polarization Type -- 10.1.2 Polarization Sensitivity -- 10.1.3 Polarization in Radar Systems -- 10.2 Polarization Scattering Matrix -- 10.2.1 Relation to RCS -- 10.2.2 Polarization Characteristics of the Scattered Wave -- 10.2.3 Polarimetric Decompositions of EM Wave Scattering -- 10.2.4 The Pauli Decomposition -- 10.2.4.1 Description of Pauli Decomposition -- 10.2.4.2 Interpretation of Pauli Decomposition -- 10.2.4.3 Polarimetric Image Representation Using Pauli Decomposition -- 10.3 Why Polarimetric ISAR Imaging? -- 10.4 ISAR Imaging with Full Polarization -- 10.4.1 ISAR Data in LP Basis -- 10.4.2 ISAR Data in CP Basis -- 10.5 Polarimetric ISAR Images -- 10.5.1 Pol-ISAR Image of a Benchmark Target -- 10.5.1.1 The "SLICY" Target -- 10.5.1.2 Fully Polarimetric EM Simulation of SLICY -- 10.5.1.3 LP Pol-ISAR Images of SLICY -- 10.5.1.4 CP Pol-ISAR Images of SLICY -- 10.5.1.5 Pauli Decomposition Image of SLICY -- 10.5.2 Pol-ISAR Image of a Complex Target -- 10.5.2.1 The "Military Tank" Target -- 10.5.2.2 Fully Polarimetric EM Simulation of "Tank" Target -- 10.5.2.3 LP Pol-ISAR Images of "Tank" Target -- 10.5.2.4 CP Pol-ISAR Images of "Tank" Target -- 10.5.2.5 Pauli Decomposition Image of "Tank" Target -- 10.6 Feature Extraction from Polarimetric Images -- 10.7 Matlab Codes -- References
6.8.2 Range and Cross-Range Resolution -- 6.8.3 Frequency Bandwidth and the Center Frequency -- 6.8.4 Doppler Frequency Bandwidth -- 6.8.5 Pulse Repetition Frequency -- 6.8.6 Coherent Integration (Dwell) Time -- 6.8.7 Pulse Width -- 6.9 Example of Chirp Pulse-Based Range-Doppler ISAR Imaging -- 6.10 Example of SFCW-Based Range-Doppler ISAR Imaging -- 6.11 Matlab Codes -- References -- Chapter 7 Scattering Center Representation of Inverse Synthetic Aperture Radar -- 7.1 Scattering/Radiation Center Model -- 7.2 Extraction of Scattering Centers -- 7.2.1 Image Domain Formulation -- 7.2.1.1 Extraction in the Image Domain: The "CLEAN" Algorithm -- 7.2.1.2 Reconstruction in the Image Domain -- 7.2.2 Fourier Domain Formulation -- 7.2.2.1 Extraction in the Fourier Domain -- 7.2.2.2 Reconstruction in the Fourier Domain -- 7.3 Matlab Codes -- References -- Chapter 8 Motion Compensation for Inverse Synthetic Aperture Radar -- 8.1 Doppler Effect Due to Target Motion -- 8.2 Standard MOCOMP Procedures -- 8.2.1 Translational MOCOMP -- 8.2.1.1 Range Tracking -- 8.2.1.2 Doppler Tracking -- 8.2.2 Rotational MOCOMP -- 8.3 Popular ISAR MOCOMP Techniques -- 8.3.1 Cross-Correlation Method -- 8.3.1.1 Example for the Cross-Correlation Method -- 8.3.2 Minimum Entropy Method -- 8.3.2.1 Definition of Entropy in ISAR Images -- 8.3.2.2 Example for the Minimum Entropy Method -- 8.3.3 JTF-Based MOCOMP -- 8.3.3.1 Received Signal from a Moving Target -- 8.3.3.2 An Algorithm for JTF-Based Rotational MOCOMP -- 8.3.3.3 Example for JTF-Based Rotational MOCOMP -- 8.3.4 Algorithm for JTF-Based Translational and Rotational MOCOMP -- 8.3.4.1 A Numerical Example -- 8.4 Matlab Codes -- References -- Chapter 9 Bistatic ISAR Imaging -- 9.1 Why Bi-ISAR Imaging? -- 9.2 Geometry for Bi-Isar Imaging and the Algorithm -- 9.2.1 Bi-ISAR Imaging Algorithm for a Point Scatterer
4.5.4.1 ISAR Design Example #1: "Aircraft Target -- 4.5.4.2 ISAR Design Example #2: "Military Tank Target -- 4.6 2D ISAR Image Formation (Wide Bandwidth, Large Angles) -- 4.6.1 Direct Integration -- 4.6.2 Polar Reformatting -- 4.7 3D ISAR Image Formation -- 4.7.1 Range and Cross-Range resolutions -- 4.7.2 A Design Example for 3D ISAR -- 4.8 Matlab Codes -- References -- Chapter 5 Imaging Issues in Inverse Synthetic Aperture Radar -- 5.1 Fourier-Related Issues -- 5.1.1 DFT Revisited -- 5.1.2 Positive and Negative Frequencies in DFT -- 5.2 Image Aliasing -- 5.3 Polar Reformatting Revisited -- 5.3.1 Nearest Neighbor Interpolation -- 5.3.2 Bilinear Interpolation -- 5.4 Zero Padding -- 5.5 Point Spread Function -- 5.6 Windowing -- 5.6.1 Common Windowing Functions -- 5.6.1.1 Rectangular Window -- 5.6.1.2 Triangular Window -- 5.6.1.3 Hanning Window -- 5.6.1.4 Hamming Window -- 5.6.1.5 Kaiser Window -- 5.6.1.6 Blackman Window -- 5.6.1.7 Chebyshev Window -- 5.6.2 ISAR Image Smoothing via Windowing -- 5.7 Matlab Codes -- References -- Chapter 6 Range-Doppler Inverse Synthetic Aperture Radar Processing -- 6.1 Scenarios for ISAR -- 6.1.1 Imaging Aerial Targets via Ground-Based Radar -- 6.1.2 Imaging Ground/Sea Targets via Aerial Radar -- 6.2 ISAR Waveforms for Range-Doppler Processing -- 6.2.1 Chirp Pulse Train -- 6.2.2 Stepped Frequency Pulse Train -- 6.3 Doppler Shift's Relation to Cross-Range -- 6.3.1 Doppler Frequency Shift Resolution -- 6.3.2 Resolving Doppler Shift and Cross-Range -- 6.4 Forming the Range-Doppler Image -- 6.5 ISAR Receiver -- 6.5.1 ISAR Receiver for Chirp Pulse Radar -- 6.5.2 ISAR Receiver for SFCW Radar -- 6.6 Quadrature Detection -- 6.6.1 I-Channel Processing -- 6.6.2 Q-Channel Processing -- 6.7 Range Alignment -- 6.8 Defining the Range-Doppler ISAR Imaging Parameters -- 6.8.1 Image Frame Dimension (Image Extends)
Title Inverse synthetic aperture radar imaging with MATLAB algorithms
URI https://cir.nii.ac.jp/crid/1130291776028088971
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