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Proceedings Paper

Recent ATR and fusion algorithm improvements for multiband sonar imagery
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Paper Abstract

An improved automatic target recognition processing string has been developed. The overall processing string consists of pre-processing, subimage adaptive clutter filtering, normalization, detection, data regularization, feature extraction, optimal subset feature selection, feature orthogonalization and classification processing blocks. The objects that are classified by the 3 distinct ATR strings are fused using the classification confidence values and their expansions as features, and using "summing" or log-likelihood-ratio-test (LLRT) based fusion rules. The utility of the overall processing strings and their fusion was demonstrated with new high-resolution three-frequency band sonar imagery. The ATR processing strings were individually tuned to the corresponding three-frequency band data, making use of the new processing improvement, data regularization; this improvement entails computing the input data mean, clipping the data to a multiple of its mean and scaling it, prior to feature extraction and resulted in a 3:1 reduction in false alarms. Two significant fusion algorithm improvements were made. First, a nonlinear exponential Box-Cox expansion (consisting of raising data to a to-be-determined power) feature LLRT fusion algorithm was developed. Second, a repeated application of a subset Box-Cox feature selection / feature orthogonalization / LLRT fusion block was utilized. It was shown that cascaded Box-Cox feature LLRT fusion of the ATR processing strings outperforms baseline "summing" and single-stage Box-Cox feature LLRT algorithms, yielding significant improvements over the best single ATR processing string results, and providing the capability to correctly call the majority of targets while maintaining a very low false alarm rate.

Paper Details

Date Published: 4 May 2009
PDF: 11 pages
Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73030C (4 May 2009); doi: 10.1117/12.818542
Show Author Affiliations
Tom Aridgides, Lockheed Martin Maritime Systems & Sensors (United States)
Manuel Fernández, Lockheed Martin Maritime Systems & Sensors (United States)

Published in SPIE Proceedings Vol. 7303:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV
Russell S. Harmon; J. Thomas Broach; John H. Holloway Jr., Editor(s)

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