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.
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