Caner Ozdemir - Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms

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Kai Chang, Editor

Texas A&M University

A complete list of the titles in this series appears at the end of this volume.

Second Edition

Caner Özdemir, Phd

Mersin UniversityMersin, Turkey

This second edition first published 2021

© 2021 John Wiley & Sons, Inc.

Edition History John Wiley & Sons, Inc. (1e, 2012)

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Library of Congress Cataloging‐in‐Publication Data

Names: Özdemir, Caner, author.

Title: Inverse synthetic aperture radar imaging with MATLAB algorithms: with advanced sar/isar imaging concepts, algorithms, and matlab codes / Caner Ozdemir, PhD Mersin University, Mersin, Turkey.

Description: 2nd edition. | Hoboken, NJ, USA : Wiley, 2021. | Series: Wiley series in microwave and optical engineering | Includes bibliographical references and index.

Identifiers: LCCN 2020031216 (print) | LCCN 2020031217 (ebook) | ISBN 9781119521334 (cloth) | ISBN 9781119521365 (adobe pdf) | ISBN 9781119521389 (epub)

Subjects: LCSH: MATLAB. | Synthetic aperture radar. | MATLAB.

Classification: LCC TK6592.S95 O93 2020 (print) | LCC TK6592.S95 (ebook) | DDC 621.3848/5–dc23

LC record available at https://lccn.loc.gov/2020031216LC ebook record available at https://lccn.loc.gov/2020031217

Cover design by Wiley

Cover image: Courtesy of Caner Özdemir, (background) © Maxiphoto/Getty Images

To:My wife Betül,My three daughters,My brother,My father,and the memory of my beloved mother

In the first edition of the book, I tried to cover most of the aspects of inverse synthetic aperture radar (ISAR) imaging starting from Fourier analysis to some advanced ISAR concepts such as range‐Doppler ISAR processing and ISAR motion compensation techniques. The main goal was to present a conceptual description of ISAR imagery and the explanation of basic ISAR research topics. Although the primary audience would be graduate students and other interested researchers in the fields of electrical engineering and physics, I hoped that colleagues working in radar research and development or in a related industry might also benefit from the book.

It has been more than eight years since the publication of the first edition. Since then, I have been really grateful that I have received positive responses from the researchers and colleagues that are interested and/or involved in radar imaging, and especially ISAR imaging. Undoubtedly, ISAR has been gaining more attention among researchers, scholars, and engineers as emerging new developments in ISAR research have been reported by various colleagues day by day.

In this second edition of the book, I have tried to include the recent progress made in ISAR imaging research and also give insights to more advanced concepts. Therefore, in this edition of the book, I have made the following alterations and additions:

All the chapters in the first edition have been revised including all the texts, equations, and figures with some additions. Typos in the first edition have also been corrected.

Chapter 3that is devoted to the issues of synthetic aperture radar (SAR) has been extended to include the SAR focusing/processing algorithms such as range‐Doppler algorithm (RDA), back‐projection algorithm (BPA) and frequency‐wave number algorithm (ω‐kA). The Matlab codes for these algorithms are being provided with the associated numerical examples. Brief explanations of other SAR focusing/processing algorithms including chirp scaling algorithm (CSA) and phase shift algorithm (PSA) have also been mentioned.

In Chapters 4, 5, 7, and 12where we handle various aspects of ISAR imaging technology, new scattered field raw data and the corresponding ISAR images that are more visually attractive are presented together with the associated Matlab codes that can be used to generate these images.

A total of three new chapters have been written to cover the topics that were not considered in the first edition and also to include more detailed subjects of ISAR imaging to be able to reflect the recent research studies. These are listed below:The “Bistatic ISAR (Bi‐ISAR) Imaging” concept is covered in Chapter 9. While the ISAR imaging algorithms presented in previous chapters are based on monostatic usage of ISAR imaging, we introduce the formulation of ISAR imaging for the bistatic usages by presenting key aspects such as resolutions in range/cross‐range directions and usage limitations. Also, extension of Bi‐ISAR to multistatic ISAR (Mu‐ISAR) imaging is derived with the associated Matlab examples. A general assessment of Bi‐ISAR and Mu‐ISAR imaging to conventional monostatic ISAR imaging is being made throughout the chapter by comparing the outcomes of quantitative metrics and giving the concluding statements about their advantages and disadvantages based on these measurable evaluations.In Chapter 10, we have added a new and exciting research topic of ISAR called “Polarimetric ISAR Imaging.” As the traditional ISAR imaging algorithms are based only on a single polarization of the backscattered electric field, we demonstrate in this chapter that very exciting features of the target can be extracted with the use of other possible polarizations for the reflected wave. Polarization decomposition techniques are being introduced and Pauli decomposition scheme is taken as the tool to be applied to the different polarization ISAR images in this book. The formulation and the usage of Pauli decomposition technique are presented together with its Matlab codes. Various realistic simulation examples based on linear polarization, circular polarization, and also Pauli decomposition are given together with obtained polarimetric ISAR images. It has been demonstrated through the examples that polarized ISAR images definitely increase the recognition and classification of targets by providing increased number of extracted target features.Thanks to the recent development in the microwave circuit technology and antenna design, ISAR imaging algorithms have been started to be used in the near‐field region. Therefore, I have added a new part entitled “Near‐field ISAR imaging” as Chapter 11. The near‐field ISAR imaging algorithms are being introduced. Two of them called “Focusing operator” and the back‐projection based focusing algorithms are given by presenting their theoretical formulation and algorithm steps together with corresponding Matlab codes. Also, numerical and measured examples based on real scenarios are being shared.