1st Edition

Compressive Sensing for Urban Radar

Edited By Moeness Amin Copyright 2015
508 Pages 196 B/W Illustrations
by CRC Press

508 Pages 196 B/W Illustrations
by CRC Press

508 Pages 196 B/W Illustrations
by CRC Press

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... Read more

Compressive Sensing Fundamentals
Michael B. Wakin
Colorado School of Mines, Golden, USA

Overcomplete Dictionary Design for Sparse Reconstruction of Building Layout Mapping
Wim van Rossum and Jacco de Wit
Netherlands Organization for Applied Scientific Research (TNO), The Hague

Compressive Sensing for Radar Imaging of Underground Targets
Kyle R. Krueger, James H. McClellan, and Waymond R. Scott, Jr.
Georgia Institute of Technology, Atlanta, USA

Wall Clutter Mitigations for Compressive Imaging of Building Interiors
Fauzia Ahmad
Villanova University, Pennsylvania, USA

Compressive Sensing for Urban Multipath Exploitation
Michael Leigsnering and Abdelhak M. Zoubir
Darmstadt University of Technology, Germany

Compressive Sensing Kernel Design for Imaging of Urban Objects
Nathan A. Goodman, Junhyeong Bae, and Yujie Gu
The University of Oklahoma, Norman, USA

Compressive Sensing for Multi-Polarization Through-Wall Radar Imaging
Abdesselam Bouzerdoum, Jack Yang, and Fok Hing Chi Tivive
University of Wollongong, New South Wales, Australia

Sparsity-Aware Human Motion Indication
Moeness G. Amin
Villanova University, Pennsylvania, USA

Time-Frequency Analysis of Micro-Doppler Signals based on Compressive Sensing
Ljubisa Stankovic, Srdjan Stankovic, Irena Orovic, and Yimin D. Zhang
University of Montenegro, Podgorica and Villanova University, Pennsylvania, USA

Urban Target Tracking using Sparse Representations
Phani Chavali and Arye Nehorai
Washington University in St. Louis, Missouri, USA

3D Imaging of Vehicles from Sparse Apertures in Urban Environment
Emre Ertin
The Ohio State University, Columbus, USA

Compressive Sensing for MIMO Urban Radar
Yao Yu and Athina Petropulu
San Diego, California, USA and Rutgers, The State University of New Jersey, Piscataway, USA

Compressive Sensing Meets Noise Radar
Mahesh C. Shastry, Ram M. Narayanan, and Muralidhar Rangaswamy
The Pennsylvania State University, State College, USA and Air Force Research Laboratory,
Wright-Patterson Air Force Base, Ohio, USA

Biography

Dr. Moeness G. Amin has been a faculty member of the Department of Electrical and Computer Engineering at Villanova University, Pennsylvania, USA for nearly 30 years. In 2002, he became the director of the Center for Advanced Communications, College of Engineering. Currently he is the chair of the Electrical Cluster of the Franklin Institute Committee on Science and the Arts, as well as an IEEE, SPIE, and IET fellow. The recipient of many prestigious awards, he has conducted extensive research in radar signal processing, authored over 650 journal and conference papers, and served as an editor for numerous publications.

"The essential feature of this book is that it brings together the areas of compressive sensing and radar imaging for urban sensing. These areas of attributes are highly relevant to promote sustainability and for a range of civil and military applications, such as search and rescue missions, hostage rescue situations, urban design, and surveillance and reconnaissance in urban environments."
—Fulvio Gini, University of Pisa, Italy