Radar for Indoor Monitoring Detection, Classification, and Assessment

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.

Introduction. Fundamentals of Indoor Radar. Radar Hardware for Indoor Monitoring. Modeling and Simulation of Human Motions for Micro-Doppler Signatures. Continuous-Wave Doppler Radar for Fall Detection. Continuous-Wave Doppler Radar for Human Gait Classification. Range-Doppler Processing for Human Motion Detection and Classification. Tracking Humans in the Indoor Multipath Environment. Bistatic Radar Configuration for Human Body and Limb Motion Detection and Classification. Microwave and Millimeter-Wave Radars for Vital Sign Monitoring. Multiple-Input Multiple-Output Radar for Monitoring of Bed-Ridden Patients. Activity Recognition and Localization Using Array Antenna: Array Sensor. Radar Monitoring of Humans with Assistive Walking Devices. Radar for Disease Detection and Monitoring. Wireless Sensing for Device-Free Recognition of Human Motion. IR Sensors for Indoor Monitoring. Index.

Moeness Amin is the Director of the Center for Advanced Communications, Villanova University, Pennsylvania, USA. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE); Fellow of the International Society of Optical Engineering; Fellow of the Institute of Engineering and Technology (IET); and Fellow of the European Association for Signal Processing. Dr. Amin is a Recipient of the 2017 Fulbright Distinguished Chair in Advanced Science and Technology, Recipient of 2016 Alexander von Humboldt Research Award, Recipient of 2016 IET Achievement Medal, Recipient of 2014 IEEE Signal Processing Society Technical Achievement Award; Recipient of the 2009 Individual Technical Achievement Award from the European Association for Signal Processing; Recipient of the IEEE Warren D White Award for Excellence in Radar Engineering; Recipient of the IEEE Third Millennium Medal; Recipient of the 2010 NATO Scientific Achievement Award; Recipient of the 2010 Chief of Naval Research Challenge Award; Recipient of Villanova University Outstanding Faculty Research Award, 1997; and the Recipient of the IEEE Philadelphia Section Award, 1997. He was a Distinguished Lecturer of the IEEE Signal Processing Society, 2003-2004, and he is currently the Chair of the Electrical Cluster of the Franklin Institute Committee on Science and the Arts. Dr. Amin has over 700 journal and conference publications in signal processing theory and applications. He co-authored 22 book chapters and is the Editor of the two books, "Through the Wall Radar Imaging" and "Compressive Sensing for Urban Radar," both published by CRC Press in 2011 and 2014, respectively.