COMPRESSIVE SENSING FOR URBAN RADAR - Plenary_Amin.pdf
Abstract : Sparsity-Aware Urban Radar
Compressive Sensing for Urban Radars, or Compressive Urban Radar (CUR), is an area of research and development which investigates the radar performance within the context of compressive sensing and with a focus on urban applications. CUR examines the effect of using significantly reduced data measurements in time, space and frequency on 2D and 3D imaging quality, strong EM reflections from exterior and interior walls, target multipath and ghosts, and moving target detection and tracking. In this respect, CUR is a hybrid between the two areas of compressive sensing and urban sensing. In essence, it enables reliable localization and imaging of indoor targets using a very small percentage of the entire data volume. Reduced or compressed observations can be due logistical difficulty in data collection or motivated by the need for fast data acquisition.
In this talk, compressive sensing will be put in context for radar, in general, and in particular for the urban environment. We will explain how CS can achieve various radar sensing goals and objectives, and how it compares with the use of full data volume. Different radar specifications and configurations will be used. In particular, we will address CS for urban radars towards achieving
Compressive Sensing for Urban Radars, or Compressive Urban Radar (CUR), is an area of research and development which investigates the radar performance within the context of compressive sensing and with a focus on urban applications. CUR examines the effect of using significantly reduced data measurements in time, space and frequency on 2D and 3D imaging quality, strong EM reflections from exterior and interior walls, target multipath and ghosts, and moving target detection and tracking. In this respect, CUR is a hybrid between the two areas of compressive sensing and urban sensing. In essence, it enables reliable localization and imaging of indoor targets using a very small percentage of the entire data volume. Reduced or compressed observations can be due logistical difficulty in data collection or motivated by the need for fast data acquisition.
In this talk, compressive sensing will be put in context for radar, in general, and in particular for the urban environment. We will explain how CS can achieve various radar sensing goals and objectives, and how it compares with the use of full data volume. Different radar specifications and configurations will be used. In particular, we will address CS for urban radars towards achieving
- (a) Imaging through walls;
- (b) Detection of behind the wall targets;
- (c) Mitigation of wall clutter; and
- (d) Exploitation of multipath.
All of the above issues will
be examined using data generated at the Radar Imaging Lab, Villanova
University.
UC San Diego /All Collec
Compressive Sensing for Urban Radar - CRC Press Book
Title | Compressive sensing for urban radar / edited by Moeness Amin |
Published | Boca Raton : CRC Press, [2014] |
Copyright | ©2015 |
"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:
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"-- Provided by publisher |
Other Author | Amin, Moeness G. editor of compilation |
Other Title | CRC Press. ENGnetBASE online monographs DDA 2014 |
CRC Press. ENVIROnetBASE online monographs 2013- | |
CRC Press. EnvironmentalSciencenetBASE online monographs 2013- | |
ISBN | 9781466597846 (hardback) |
1466597844 (hardback) | |
9781466597853 | |
An Introduction To Compressive Sampling.pdf Contents:
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