Compressive Sensing and Its Applications in Radar Imaging and Rough Surface Scattering
Compressive Sensing and Its Applications in Radar Imaging and Rough Surface Scattering

Author: Hsiao-Chieh Tseng

Publisher:

Published: 2011

Total Pages:

ISBN-13: 9781267239914

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Compressive sensing is a rapidly growing research field which brings a huge amount of applications in science and engineering, and leads breakthrough in the study of signal processing, imaging, tomography, and related fields therein. In this dissertation, brief summaries of compressive sensing and important results from literatures will be reviewed. Next, its applications in radar imaging and rough surface scattering problem are discussed. Various radar sensing schemes are designed andformulated in the the framework of compressive sensing, giving the estimates of measurements and target recoverability by linear or quadratic chirps. Next, the rough surface scattering problems are studied. After a review of the mathematical setup of rough surface scattering and its numerical methods, the main result for inverse rough surface scattering and numerical simulations are demonstrated. It is shown that, with Rayleigh hypothesis and suitable designed scheme, one can reconstruct the angular spectrum for the periodic rough surface and then the surface profile, with subwavelength structures. The sparsity of the angular spectra is studied as well as the Fourier series expansion of the surface profile.

Radar Scattering and Imaging of Rough Surfaces
Radar Scattering and Imaging of Rough Surfaces

Author: Kun-Shan Chen

Publisher: CRC Press

Published: 2020-11-19

Total Pages: 323

ISBN-13: 1351011561

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Radar scattering and imaging of rough surfaces is an active interdisciplinary area of research with many practical applications in fields such as mineral and resource exploration, ocean and physical oceanography, military and national defense, planetary exploration, city planning and land use, environmental science, and many more. By focusing on the most advanced analytical and numerical modeling and describing both forward and inverse modeling, Radar Scattering and Imaging of Rough Surfaces: Modeling and Applications with MATLAB® connects the scattering process to imaging techniques by vivid examples through numerical and experimental demonstrations and provides computer codes and practical uses. This book is unique in its simultaneous treatment of radar scattering and imaging. Key Features Bridges physical modeling with simulation for resolving radar imaging problems (the first comprehensive work to do so) Provides excellent basic and advanced information for microwave remote-sensing professionals in various fields of science and engineering Covers most advanced analytical and numerical modeling for both backscattering and bistatic scattering Includes MATLAB® codes useful not only for academics but also for radar engineers and scientists to develop tools applicable in different areas of earth studies Covering both the theoretical and the practical, Radar Scattering and Imaging of Rough Surfaces: Modeling and Applications with MATLAB® is an invaluable resource for professionals and students using remote sensing to study and explain the Earth and its processes. University and research institutes, electrical and radar engineers, remote-sensing image users, application software developers, students, and academics alike will benefit from this book. The author, Kun-Shan Chen, is an internationally known and respected engineer and scientist and an expert in the field of electromagnetic modeling.

Compressive Sensing for Urban Radar
Compressive Sensing for Urban Radar

Author: Moeness Amin

Publisher: CRC Press

Published: 2017-12-19

Total Pages: 508

ISBN-13: 1466597852

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With the emergence of compressive sensing and sparse signal reconstruction, approaches to urban radar have shifted toward relaxed constraints on signal sampling schemes in time and space, and to effectively address logistic difficulties in data acquisition. Traditionally, these challenges have hindered high resolution imaging by restricting both bandwidth and aperture, and by imposing uniformity and bounds on sampling rates. Compressive Sensing for Urban Radar is the first book to focus on a hybrid of two key areas: compressive sensing and urban sensing. It explains how reliable imaging, tracking, and localization of indoor targets can be achieved using compressed observations that amount to a tiny percentage of the entire data volume. Capturing the latest and most important advances in the field, this state-of-the-art text: Covers both ground-based and airborne synthetic aperture radar (SAR) and uses different signal waveforms Demonstrates successful applications of compressive sensing for target detection and revealing building interiors Describes problems facing urban radar and highlights sparse reconstruction techniques applicable to urban environments Deals with both stationary and moving indoor targets in the presence of wall clutter and multipath exploitation Provides numerous supporting examples using real data and computational electromagnetic modeling Featuring 13 chapters written by leading researchers and experts, Compressive Sensing for Urban Radar is a useful and authoritative reference for radar engineers and defense contractors, as well as a seminal work for graduate students and academia.

Radar Scattering and Imaging of Rough Surfaces
Radar Scattering and Imaging of Rough Surfaces

Author: K. S. Chen

Publisher: CRC Press

Published: 2020-11-20

Total Pages: 323

ISBN-13: 9781138541269

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Radar scattering and imaging of rough surfaces is an active interdisciplinary area of research with many practical applications in fields such as mineral and resource exploration, ocean and physical oceanography, military and national defense, planetary exploration, city planning and land use, environmental science, and many more. By focusing on the most advanced analytical and numerical modeling and describing both forward and inverse modeling, Radar Scattering and Imaging of Rough Surfaces: Modeling and Applications with MATLAB(R) connects the scattering process to imaging techniques by vivid examples through numerical and experimental demonstrations and provides computer codes and practical uses. This book is unique in its simultaneous treatment of radar scattering and imaging. Key Features Bridges physical modeling with simulation for resolving radar imaging problems (the first comprehensive work to do so) Provides excellent basic and advanced information for microwave remote-sensing professionals in various fields of science and engineering Covers most advanced analytical and numerical modeling for both backscattering and bistatic scattering Includes MATLAB(R) codes useful not only for academics but also for radar engineers and scientists to develop tools applicable in different areas of earth studies Covering both the theoretical and the practical, Radar Scattering and Imaging of Rough Surfaces: Modeling and Applications with MATLAB(R) is an invaluable resource for professionals and students using remote sensing to study and explain the Earth and its processes. University and research institutes, electrical and radar engineers, remote-sensing image users, application software developers, students, and academics alike will benefit from this book. The author, Kun-Shan Chen, is an internationally known and respected engineer and scientist and an expert in the field of electromagnetic modeling.

Remote Sensing with Imaging Radar
Remote Sensing with Imaging Radar

Author: John A. Richards

Publisher: Springer Science & Business Media

Published: 2009-10-08

Total Pages: 376

ISBN-13: 3642020208

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This book is concerned with remote sensing based on the technology of imaging radar. It assumes no prior knowledge of radar on the part of the reader, commencing with a treatment of the essential concepts of microwave imaging and progressing through to the development of multipolarisation and interferometric radar, modes which underpin contemporary applications of the technology. The use of radar for imaging the earth’s surface and its resources is not recent. Aircraft-based microwave systems were operating in the 1960s, ahead of optical systems that image in the visible and infrared regions of the spectrum. Optical remote sensing was given a strong impetus with the launch of the first of the Landsat series of satellites in the mid 1970s. Although the Seasat satellite launched in the same era (1978) carried an imaging radar, it operated only for about 12 months and there were not nearly so many microwave systems as optical platforms in service during the 1980s. As a result, the remote sensing community globally tended to develop strongly around optical imaging until Shuttle missions in the early to mid 1980s and free-flying imaging radar satellites in the early to mid 1990s became available, along with several sophisticated aircraft platforms. Since then, and particularly with the unique capabilities and flexibility of imaging radar, there has been an enormous surge of interest in microwave imaging technology. Unlike optical imaging, understanding the theoretical underpinnings of imaging radar can be challenging, particularly when new to the field.

Compressed Sensing in Radar Signal Processing
Compressed Sensing in Radar Signal Processing

Author: Antonio De Maio

Publisher: Cambridge University Press

Published: 2019-10-17

Total Pages: 381

ISBN-13: 110857694X

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Learn about the most recent theoretical and practical advances in radar signal processing using tools and techniques from compressive sensing. Providing a broad perspective that fully demonstrates the impact of these tools, the accessible and tutorial-like chapters cover topics such as clutter rejection, CFAR detection, adaptive beamforming, random arrays for radar, space-time adaptive processing, and MIMO radar. Each chapter includes coverage of theoretical principles, a detailed review of current knowledge, and discussion of key applications, and also highlights the potential benefits of using compressed sensing algorithms. A unified notation and numerous cross-references between chapters make it easy to explore different topics side by side. Written by leading experts from both academia and industry, this is the ideal text for researchers, graduate students and industry professionals working in signal processing and radar.

2016 4th International Workshop on Compressed Sensing Theory and Its Applications to Radar, Sonar and Remote Sensing (CoSeRa)
2016 4th International Workshop on Compressed Sensing Theory and Its Applications to Radar, Sonar and Remote Sensing (CoSeRa)

Author: IEEE Staff

Publisher:

Published: 2016-09-19

Total Pages:

ISBN-13: 9781509029211

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The aim of CoSeRa is to bring experts of Compressive Sensing (CS)and radar sonar EO IR signal processing and remote sensing together to explore the state of the art in development of CS techniques for different areas of applications and to turn out its advantages or possible drawbacks compared to classical solutions

Multi-Dimensional Imaging with Synthetic Aperture Radar
Multi-Dimensional Imaging with Synthetic Aperture Radar

Author: Gianfranco Fornaro

Publisher: Elsevier

Published: 2024-02-12

Total Pages: 392

ISBN-13: 0128216573

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Multi-Dimensional Imaging with Synthetic Aperture Radar: Theory and Applications provides a complete description of principles, models and data processing methods, giving an introduction to the theory that underlies recent applications such as topographic mapping and natural risk situational awareness – seismic-tectonics, active volcano, landslides and subsidence monitoring - security, urban, wide area and infrastructure control. Imaging radars, specifically Synthetic Aperture Radar (SAR), generally mounted onboard satellites or airplanes, are able to provide systematic high-resolution imaging of the Earth's surface. Recent advances in the field has seen applications to natural risk monitoring and security and has driven the development of many operational systems. Explains the modeling and data processing involved in interferometric and tomographic SAR Shows the potential and limitations of using SAR technology in several applications Presents the link between basic signal processing concepts and state-of-the-art capabilities in imaging radars Explains the use of basic SAR processing tools and datasets

Compressed Sensing and Its Applications
Compressed Sensing and Its Applications

Author: Holger Boche

Publisher:

Published: 2015

Total Pages:

ISBN-13: 9783319160436

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Since publication of the initial papers in 2006, compressed sensing has captured the imagination of the international signal processing community, and the mathematical foundations are nowadays quite well understood. Parallel to the progress in mathematics, the potential applications of compressed sensing have been explored by many international groups of, in particular, engineers and applied mathematicians, achieving very promising advances in various areas such as communication theory, imaging sciences, optics, radar technology, sensor networks, or tomography. Since many applications have reached a mature state, the research center MATHEON in Berlin focusing on "Mathematics for Key Technologies", invited leading researchers on applications of compressed sensing from mathematics, computer science, and engineering to the "MATHEON Workshop 2013: Compressed Sensing and its Applications" in December 2013. It was the first workshop specifically focusing on the applications of compressed sensing. This book features contributions by the plenary and invited speakers of this workshop. To make this book accessible for those unfamiliar with compressed sensing, the book will not only contain chapters on various applications of compressed sensing written by plenary and invited speakers, but will also provide a general introduction into compressed sensing. The book is aimed at both graduate students and researchers in the areas of applied mathematics, computer science, and engineering as well as other applied scientists interested in the potential and applications of the novel methodology of compressed sensing. For those readers who are not already familiar with compressed sensing, an introduction to the basics of this theory will be included.