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Proceedings Paper

Phenomenology metric development for SAR scene modeling tools
Author(s): Patricia A. Ryan; Kelce S. Wilson
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Paper Abstract

Synthetic Aperture Radar (SAR) image modeling tools are of high interest to Automatic Target Recognition (ATR) algorithm evaluation because they allow the testing of ATRs over a wider range of extended operating conditions (EOCs). Typical EOCs include target aspect, target configuration, target obscuration, and background terrain variations. Since the phenomenology fidelity of the synthetic prediction techniques is critical for ATR evaluation, metric development for complex scene prediction is needed for accurate ATR performance estimation. An image domain hybrid prediction technique involves the insertion of a synthetic target chip into a measured image background. Targets in terrain scenes will be predicted and compared with similar measured data scenarios. Shadow region histograms and terrain region histograms will be used to develop some first generation metrics for phenomenology validation of hybrid SAR prediction techniques.

Paper Details

Date Published: 13 August 1999
PDF: 7 pages
Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999);
Show Author Affiliations
Patricia A. Ryan, Air Force Research Lab. (United States)
Kelce S. Wilson, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 3721:
Algorithms for Synthetic Aperture Radar Imagery VI
Edmund G. Zelnio, Editor(s)

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