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Proceedings Paper

Alternative procedure for detecting stationary targets with ultrawideband foliage-penetration radar
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Paper Abstract

The Army Research Laboratory has investigated various phenomenology-based approaches for improving the detection of targets in wide-angle, ultra-wideband foliage penetration synthetic aperture radar (SAR) data. The approach presented here exploits the aspect-dependent reflectivity of vehicles, by filtering the SAR image data to obtain sub-aperture images from the original full-aperture radar image. These images represent the images of the target as seen by the sub-aperture SAR from two different locations (squint angles). We present a straightforward approach to extending an existing collection of features for a quadratic polynomial discriminator with features calculated from these two, lower-resolution sub-aperture SAR data images. We describe a method for generating the modified features and assess their potential contribution to improved probability of detection.

Paper Details

Date Published: 27 August 2001
PDF: 10 pages
Proc. SPIE 4382, Algorithms for Synthetic Aperture Radar Imagery VIII, (27 August 2001); doi: 10.1117/12.438211
Show Author Affiliations
Kenneth I. Ranney, Army Research Lab. (United States)
Hiralal Khatri, Army Research Lab. (United States)
Lam H. Nguyen, Army Research Lab. (United States)

Published in SPIE Proceedings Vol. 4382:
Algorithms for Synthetic Aperture Radar Imagery VIII
Edmund G. Zelnio, Editor(s)

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