Paper
19 May 2005 Information theoretic bounds of ATR algorithm performance for sidescan sonar target classification
Vincent L. Myers, Marc A. Pinto
Author Affiliations +
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.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vincent L. Myers and Marc A. Pinto "Information theoretic bounds of ATR algorithm performance for sidescan sonar target classification", Proc. SPIE 5807, Automatic Target Recognition XV, (19 May 2005); https://doi.org/10.1117/12.600505
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Cited by 5 scholarly publications.
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KEYWORDS
Automatic target recognition

Detection and tracking algorithms

Distortion

Target recognition

Sensors

Image resolution

Algorithm development

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