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Optical Engineering

Knowledge- and model-based automatic target recognition algorithm adaptation
Author(s): Firooz A. Sadjadi; Hatem N. Nasr; Hossien Amehdi; Michael E. Bazakos
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Paper Abstract

One ofthe most critical problems in automatic target recognition (ATR) systems is multiscenario adaptation. Today's ATR systems perform unpredictably, i.e., perform well in certain scenarios and poorly in others. Unless ATR systems can be made adaptable, their utility in battlefield missions remains questionable. We have developed a novel method called knowledge- and model-based algorithm adaptation (KMBAA). KMBAA automatically adapts the ATR parameters as the scenario changes so that ATR can maintain optimum performance. The KMBAA approach has been tested with a nonreal-time ATR simulation system and has demonstrated a significant improvement in detection, false alarm rate reduction, and segmentation accuracy performance.

Paper Details

Date Published: 1 February 1991
PDF: 6 pages
Opt. Eng. 30(2) doi: 10.1117/12.55788
Published in: Optical Engineering Volume 30, Issue 2
Show Author Affiliations
Firooz A. Sadjadi
Hatem N. Nasr, Honeywell Inc. (United States)
Hossien Amehdi, Honeywell Inc. (United States)
Michael E. Bazakos, Honeywell Inc. (United States)

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