Translator Disclaimer
15 September 1998 Ultrawideband radar target discrimination utilizing an advanced feature set
Author Affiliations +
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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lam H. Nguyen, Ravinder Kapoor, David C. Wong, and Jeffrey Sichina "Ultrawideband radar target discrimination utilizing an advanced feature set", Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); doi: 10.1117/12.321834; https://doi.org/10.1117/12.321834
PROCEEDINGS
18 PAGES


SHARE
Advertisement
Advertisement
Back to Top