DocumentCode
3517538
Title
Using complex-valued ICA to efficiently combine radar polarimetric data for target detection
Author
Novey, Mike ; Adali, Tülay
Author_Institution
Univ. of Maryland Baltimore County, Baltimore, MD
fYear
2009
fDate
19-24 April 2009
Firstpage
1673
Lastpage
1676
Abstract
Target detection in sea clutter is a challenging problem in radar detection, specifically, when the Doppler return of the target and clutter are collocated. Polarization diverse radars provide additional information that enhances target detection. In this paper, we use an effective independent component analysis (ICA) approach, adaptive complex maximization of non-Gaussianity (A-CMN), to efficiently combine polarimetric radar data prior to detection. We show that A-CMN estimates the polarimetric scatter coefficients for the single target in clutter case, thereby providing matched-filter performance without the need for clutter or target models. The detection performance using ICA is evaluated with sea clutter collected with the McMaster IPIX radar off the coast of Canada. We also demonstrates the ability of this approach to adapt to the changing sea clutter conditions using simulation results.
Keywords
independent component analysis; matched filters; object detection; radar clutter; radar detection; radar polarimetry; Canada; combine radar polarimetric data; independent component analysis approach; matched-filter; nonGaussianity adaptive complex maximization; polarimetric scatter coefficient; polarization diverse radar; radar detection; sea clutter; target detection; Doppler radar; Independent component analysis; Object detection; Polarization; Radar applications; Radar clutter; Radar detection; Radar imaging; Radar polarimetry; Random variables; ICA; Nonlinear estimation; radar detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location
Taipei
ISSN
1520-6149
Print_ISBN
978-1-4244-2353-8
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2009.4959923
Filename
4959923
Link To Document