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Proceedings Paper

Studies in adaptive automated underwater sonar mine detection and classification- part 1: exploitation methods
Author(s): Firooz A. Sadjadi
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Paper Abstract

This paper summarizes part of a study to address the issue of underwater automatic object detection and classification of mine-like objects by means of a sonar sensor. The ultimate goals were to develop methods to adaptively selects the optimum algorithms and their parameters as sensor parameters and environmental conditions change. For adaptation, the method exploits predictive performance models of target detection and classification in terms of sea state, sensor and environmental parameters, target detection and classification algorithms and their internal parameters. This paper is the first in a number of upcoming reports and describes a number of key exploitation algorithms that were used and their sample performance results. In the future, separate papers will address the performance estimation and adaptation aspects of this study.

Paper Details

Date Published: 19 June 2015
PDF: 16 pages
Proc. SPIE 9476, Automatic Target Recognition XXV, 94760K (19 June 2015); doi: 10.1117/12.2183138
Show Author Affiliations
Firooz A. Sadjadi, Lockheed Martin Corp. (United States)


Published in SPIE Proceedings Vol. 9476:
Automatic Target Recognition XXV
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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