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Proceedings Paper

Target detection in SAR: parallel algorithms, context extraction, and region-adaptive techniques
Author(s): William Phillips; Rama Chellappa
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Paper Abstract

This paper summarizes recent results in several areas of SAR target detection. We present detection algorithms designed for parallel computation and a multiresolution segmentation algorithm used to extract the context of target detections and adapt the detection algorithms to the regions being processed. We consider cell averaging and order statistic constant false alarm rate (CFAR) detectors with a Weibull clutter background on SIMD linear arrays with simple fixed point arithmetic units.After considering the parallel computation of the various CFAR algorithms, we focus on the problem of segmenting the SAR imagery to obtain the context of the detections and to adapt the detector parameters for the area under test. Our multiresolution segmentation uses maximum likelihood estimation possibly followed by the iterative conditional modes algorithm at each resolution with merging accomplished using confidence levels. The algorithms are tested on 1 ft resolution SAR intensity images taken from the TESAR sensor onboard the Predator unmanned aerial vehicle.

Paper Details

Date Published: 28 July 1997
PDF: 12 pages
Proc. SPIE 3070, Algorithms for Synthetic Aperture Radar Imagery IV, (28 July 1997); doi: 10.1117/12.281584
Show Author Affiliations
William Phillips, Northrop Grumman Corp. (United States)
Rama Chellappa, Univ. of Maryland/College Park (United States)


Published in SPIE Proceedings Vol. 3070:
Algorithms for Synthetic Aperture Radar Imagery IV
Edmund G. Zelnio, Editor(s)

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