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      Book

      Compressive Sensing for Urban Radar
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      Book

      Compressive Sensing for Urban Radar

      DOI link for Compressive Sensing for Urban Radar

      Compressive Sensing for Urban Radar book

      Compressive Sensing for Urban Radar

      DOI link for Compressive Sensing for Urban Radar

      Compressive Sensing for Urban Radar book

      ByMoeness Amin
      Edition 1st Edition
      First Published 2015
      eBook Published 31 January 2017
      Pub. Location Boca Raton
      Imprint CRC Press
      DOI https://doi.org/10.1201/b17252
      Pages 508
      eBook ISBN 9781315215563
      Subjects Engineering & Technology
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      Amin, M. (2015). Compressive Sensing for Urban Radar (1st ed.). CRC Press. https://doi.org/10.1201/b17252

      ABSTRACT

      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.

      TABLE OF CONTENTS

      chapter 1|47 pages

      Compressive Sensing Fundamentals

      ByMichael B. Wakin

      chapter 2|38 pages

      Overcomplete Dictionary Design for Building Feature Extraction

      ByWim van Rossum, Jacco de Wit

      chapter 3|35 pages

      Compressive Sensing for Radar Imaging of Underground Targets

      ByKyle R. Krueger, James H. McClellan, Waymond R. Scott

      chapter 4|29 pages

      Wall Clutter Mitigations for Compressive Imaging of Building Interiors

      ByFauzia Ahmad

      chapter 5|43 pages

      Compressive Sensing for Urban Multipath Exploitation

      ByMichael Leigsnering, Abdelhak M. Zoubir

      chapter 6|33 pages

      Measurement Kernel Design for HRR Imaging of Urban Objects

      ByNathan A. Goodman, Yujie Gu, Junhyeong Bae

      chapter 7|20 pages

      Compressive Sensing for Multipolarization through-the-Wall Radar Imaging

      ByAbdesselam Bouzerdoum, Jack Yang, Fok Hing Chi Tivive

      chapter 8|32 pages

      Sparsity-Aware Human Motion Indication

      ByMoeness G. Amin

      chapter 9|44 pages

      Time–Frequency Analysis of Micro-Doppler Signals Based on Compressive Sensing

      ByLjubiŝa Stanković, Srdjan Stanković, Irena Orović, Yimin D. Zhang

      chapter 10|33 pages

      Urban Target Tracking Using Sparse Representations*

      ByPhani Chavali, Arye Nehorai

      chapter 11|26 pages

      Three-Dimensional Imaging of Vehicles from Sparse Apertures in Urban Environment

      ByEmre Ertin

      chapter 12|41 pages

      Compressive Sensing for MIMO Urban Radar

      ByYao Yu, Athina Petropulu, Rabinder N. Madan

      chapter 13|31 pages

      Compressive Sensing Meets Noise Radar

      ByMahesh C. Shastry, Ram M. Narayanan, Muralidhar Rangaswamy
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