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.

This book aims to capture recent advances and breakthroughs in in-home radar monitoring of human motions and activities. It addresses three key attributes of radar for in-door human monitoring, namely: motion classification including fall, detection of vital signs, and categorization of human gait for risk assessment and progression of physical impairments and disabilities. It explores recent developments in radar technology for human monitoring inside homes and residences. The reader will learn enhanced detection and classification techniques of radar signals associated with human micro- and macro-motions. Furthermore, the book includes examples using real data collected from healthy individuals, patients, and retirement communities based on the subject Doppler and range information, and using different single and multi-antenna radar system configurations. Results are also presented using modeled data based on biomechanics and kinematics. Indoor monitoring is further demonstrated using alternative technologies of infrared sensors and RF signals of opportunities.

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
• 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.

This book aims to capture recent advances and breakthroughs in in-home radar monitoring of human motions and activities. It addresses three key attributes of radar for in-door human monitoring, namely: motion classification including fall, detection of vital signs, and categorization of human gait for risk assessment and progression of physical impairments and disabilities. It explores recent developments in radar technology for human monitoring inside homes and residences. The reader will learn enhanced detection and classification techniques of radar signals associated with human micro- and macro-motions. Furthermore, the book includes examples using real data collected from healthy individuals, patients, and retirement communities based on the subject Doppler and range information, and using different single and multi-antenna radar system configurations. Results are also presented using modeled data based on biomechanics and kinematics. Indoor monitoring is further demonstrated using alternative technologies of infrared sensors and RF signals of opportunities.