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Proceedings Paper

Ultrawideband radar target discrimination utilizing an advanced feature set
Author(s): Lam H. Nguyen; Ravinder Kapoor; David C. Wong; Jeffrey Sichina
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Paper Abstract

The Army Research Laboratory, as part of its mission-funded applied research program, has been evaluating the utility of a low-frequency, ultra wideband imaging radar to detect tactical vehicles concealed by foliage. Measurement programs conducted at Aberdeen Proving Grounds and elsewhere have yielded a significant and unique database of extremely wideband and (in some cases) fully polarimetric data. Prior work has concentrated on developing computationally efficient methods to quickly canvass large quantities of data to identify likely target occurrences--often called `prescreening.' This paper reviews recent findings from our phenomenology/detection efforts. Included is a reformulated prescreener that has been trained and tested against a significantly larger data set than was used in the prior work. Also discussed are initial efforts aimed at the discrimination of targets from the difficult clutter remaining after prescreening. Performance assessments are included that detail detection rates versus false alarm levels.

Paper Details

Date Published: 15 September 1998
PDF: 18 pages
Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); doi: 10.1117/12.321834
Show Author Affiliations
Lam H. Nguyen, Army Research Lab. (United States)
Ravinder Kapoor, Army Research Lab. (United States)
David C. Wong, Army Research Lab. (United States)
Jeffrey Sichina, Army Research Lab. (United States)

Published in SPIE Proceedings Vol. 3370:
Algorithms for Synthetic Aperture Radar Imagery V
Edmund G. Zelnio, Editor(s)

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