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Proceedings Paper

Information theoretic bounds of ATR algorithm performance for sidescan sonar target classification
Author(s): Vincent L. Myers; Marc A. Pinto
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Paper Abstract

With research on autonomous underwater vehicles for minehunting beginning to focus on cooperative and adaptive behaviours, some effort is being spent on developing automatic target recognition (ATR) algorithms that are able to operate with high reliability under a wide range of scenarios, particularly in areas of high clutter density, and without human supervision. Because of the great diversity of pattern recognition methods and continuously improving sensor technology, there is an acute requirement for objective performance measures that are independent of any particular sensor, algorithm or target definitions. This paper approaches the ATR problem from the point of view of information theory in an attempt to place bounds on the performance of target classification algorithms that are based on the acoustic shadow of proud targets. Performance is bounded by analysing the simplest of shape classification tasks, that of differentiating between a circular and square shadow, thus allowing us to isolate system design criteria and assess their effect on the overall probability of classification. The information that can be used for target recognition in sidescan sonar imagery is examined and common information theory relationships are used to derive properties of the ATR problem. Some common bounds with analytical solutions are also derived.

Paper Details

Date Published: 19 May 2005
PDF: 11 pages
Proc. SPIE 5807, Automatic Target Recognition XV, (19 May 2005); doi: 10.1117/12.600505
Show Author Affiliations
Vincent L. Myers, NATO Undersea Research Ctr. (Italy)
Marc A. Pinto, NATO Undersea Research Ctr. (Italy)

Published in SPIE Proceedings Vol. 5807:
Automatic Target Recognition XV
Firooz A. Sadjadi, Editor(s)

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