Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms. Caner Ozdemir
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Название: Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms

Автор: Caner Ozdemir

Издательство: John Wiley & Sons Limited

Жанр: Отраслевые издания

Серия:

isbn: 9781119521389

isbn:

СКАЧАТЬ 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.

       In Chapter 12 in which some examples based on SAR/ISAR imaging technologies are provided, I have previously introduced algorithms called antenna SAR (ASAR) and antenna coupling SAR (ACSAR) as the unique radar imaging algorithms to image antenna mounted on a platform‐to‐radar receiver interaction over the target and to image platform coupling over the antennas mounted on a target, respectively. In this edition of the book, I have added some new applications such as ground‐penetrating radar (GPR) and through‐the‐wall imaging radar (TWIR) that also make use of SAR/ISAR imaging algorithms. Measured examples of GPR and TWIR radar images are provided to demonstrate how SAR/ISAR imaging algorithms can be effectively used in some popular radar imaging applications.

      I hope that, with the new edition of the book “Inverse Synthetic Aperture Radar Imaging with MATLAB Algorithms,” the reader would benefit more in terms of abovementioned new ISAR imaging topics and also from the Matlab codes provided at the end of chapters.

      All MATLAB files may be accessed on the following FTP site: ftp://ftp.wiley.com/public/sci_tech_med/inverse_synthetic.

      Caner Özdemir Mersin, October 2020

      Acknowledgments

      I would like to address special thanks to the people below for their help and support during the preparation of this book. First, I am thankful to my wife, Betül and my three children for their patience and continuous support while writing this book. I am very grateful to Dr. Hao Ling, Emeritus Professor in Engineering of the University of Texas at Austin for being a valuable source of knowledge, ideas, and also inspiration throughout my academic carreer. He has been a great advisor since I met him, and his guidance on scientific research is priceless to me.

      I would like to express my sincere thanks to my former graduate students; Dr. Şevket Demirci, Dr. Enes Yiğit, Dr. Betül Yılmaz, Dr. Deniz Üstün, Özkan Kırık, and Dr. Hakan Işıker who have helped carrying out some of the research presented in this book. I would also like to thank my graduate student Rasheed Khankan for his help in preparing references.

      Last but not least, I would like to convey my special thanks to Dr. Kai Chang for inviting me to write the first and then second edition of the book. Without his kind offer, this book project would not have been possible.

       Caner Özdemir

      Acronyms

      Fourier transform (FT) is a common and useful mathematical tool that is utilized in innumerous applications in science and technology. FT is quite practical especially for characterizing nonlinear functions in nonlinear systems, analyzing random signals, and solving linear problems. FT is also a very important tool in radar imaging applications as we shall investigate in the forthcoming chapters of this book. Before starting to deal with the FT and inverse Fourier transform (IFT), a brief history of this useful linear operator, and СКАЧАТЬ