T04 — Sparsity-aware through-the-wall radar imaging

Summary form only given. Through-the-Wall Radar Imaging (TWRI) and Urban Sensing is an emerging technology that provides vision into otherwise obscured areas, thereby, facilitating information-gathering and intelligent decision-making. The objectives of TWRI include the determination of the building layouts, discerning the intent of activities inside the building, or detecting, locating, tracking, and imaging of targets inside enclosed structures. These three areas of attributes are highly desirable for a range of civil and military applications, examples being search and rescue missions, hostage rescue situations, and surveillance and reconnaissance in urban environments. The ultimate goal in these applications is to achieve situational awareness in an efficient and reliable manner. This goal is primarily challenged by the growing demand on radar systems to deliver high-resolution images and more accurate information. This demand, in turn, results in a significant increase in the number of data samples to be recorded, stored, and subsequently processed. Further, logistic constraints may render some of the data observations in time, space, and frequency difficult or impossible to attain. Such difficulty may be attributed to interference within a frequency band or at specific frequencies, and also due to the inability of the electromagnetic waves to reach the behind-the-wall scene from certain aspect angles. The emerging field of Compressive Sensing (CS) provides a new perspective for expediting data acquisition and alleviating processing bottlenecks in radar imaging without compromising the image quality. Towards the objective of providing quick turnaround and reliable situational awareness in urban environments, these techniques yield efficient sensing operations that allow high-resolution imaging of sparse scenes. In this tutorial, we present a comprehensive treatment of TWRI under compressive illuminations. More specifically, focus will be on CS based approaches- to streamline data acquisition with much fewer space-time samples and to provide high-resolution imaging capability for both stationary and moving target detection and localization under challenging urban environments. The discussed methodologies are an integral part of candidate solutions to pressing problems facing the TWRI and urban sensing technology.