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Proceedings Paper

Automated adaptation for ATR algorithms
Author(s): Peter F. Symosek; Michael E. Bazakos
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Paper Abstract

For an automatic target recognition (ATR) technology contract, sponsored by the US Marine Corps Systems Command, and by Coastal Systems Station, Honeywell designed, mapped to Khoros, and evaluated state-of-the-art algorithms for target discrimination from an airborne platform. Honeywell's baseline approach to improve traditional algorithm robustness is to use a functional maximization approach for representations of algorithm performance as a function of image metrics and algorithm parameters. Revised ATR parameter values are established by a hillclimbing algorithm that revises the ATR algorithm parameter values in the direction of the largest gradient of the function, thus attaining improved performance for a greater variety of scenarios than those for which the system was trained. The baseline ATR algorithms implemented for this program are designed to effectively exploit spectral features to enhance target cueing reliability. An innovative approach for the mapping of three of the individual waveband images from an array of multispectral images into a feature map which obtains high target versus background contrast is discussed. Experimental results are shown for flight test imagery.

Paper Details

Date Published: 20 June 1995
PDF: 12 pages
Proc. SPIE 2496, Detection Technologies for Mines and Minelike Targets, (20 June 1995); doi: 10.1117/12.211368
Show Author Affiliations
Peter F. Symosek, Honeywell Technology Ctr. (United States)
Michael E. Bazakos, Honeywell Technology Ctr. (United States)

Published in SPIE Proceedings Vol. 2496:
Detection Technologies for Mines and Minelike Targets
Abinash C. Dubey; Ivan Cindrich; James M. Ralston; Kelly A. Rigano, Editor(s)

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