DocumentCode :
2811200
Title :
Angle-Doppler processing using sparse regularization
Author :
Selesnick, Ivan W. ; Pillai, S. Unnikrishna ; Li, Ke Yong ; Himed, Braham
Author_Institution :
Polytech. Inst. of New York Univ., Brooklyn, NY, USA
fYear :
2010
fDate :
14-19 March 2010
Firstpage :
2750
Lastpage :
2753
Abstract :
The detection of moving objects on the ground by airborne radar is one application of space-time adaptive processing (STAP). The goal is to estimate the position and velocity of objects. This paper considers the problem as a linear inverse problem and uses ℓ1-norm regularization to promote sparsity in the solution. It is proposed that the angle-Doppler plane be explicitly segmented into the clutter ridge component and a non-clutter-ridge component. We propose that the second component be modeled as sparse - as the moving objects are assumed to be well isolated in the angle-Doppler plane.
Keywords :
Doppler radar; airborne radar; inverse problems; object detection; position measurement; radar clutter; radar imaging; space-time adaptive processing; velocity measurement; ℓ1-norm regularization; airborne radar; angle-Doppler plane processing; clutter ridge component; ground moving object detection; linear inverse problem; nonclutter ridge component; position estimation; space-time adaptive processing; sparse regularization; velocity estimation; Airborne radar; Clutter; Inverse problems; Iterative algorithms; Layout; Object detection; Radar applications; Radar detection; Sensor arrays; Signal processing algorithms; GMTI; STAP; iterated thresholding; radar; signal restoration; sparsity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
ISSN :
1520-6149
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2010.5496219
Filename :
5496219
Link To Document :
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