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.

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 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 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