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Proceedings Paper

Adaptive clutter suppression, sea mine detection/classification, and fusion processing string for sonar imagery
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Paper Abstract

An advanced, automatic, adaptive clutter suppression, sea mine detection-classification and fusion processing string has been developed and tested with sonar imagery data. The overall string includes pre-processing, adaptive clutter filtering (ACF), normalization, detection, feature extraction, classification and fusion processing blocks. The ACF is a multi-dimensional adaptive linear FIR filter, optimal in the Least Squares sense, and is applied to low- resolution data. It performs simultaneous background clutter suppression and preservation of an average peak target signature. Following 2D normalization, the detection consists of thresholding, clustering of exceedances and limiting the number of detections. Subsequently, features are extracted from high-resolution data and an orthogonalization transformation is applied to the features, enabling an efficient application of the optimal log- likelihood-ratio-test (LLRT) classification rule. Finally, the classified objects of the LF and HF processing strings are fused. The utility of the overall processing string was demonstrated with two new shallow water high-resolution sonar imagery datasets. The processing string classification performance was optimized by appropriately selecting a subset of the original feature set. The overall ACF, detection, feature extraction and orthogonalization, LLRT- based classification and fusion processing string resulted in improved mine classification capability, providing a three-fold false alarm rate reduction, compared to previous results. A wide-sense stationary covariance model was utilized in the ACF algorithm design, significantly reducing the algorithm implementation complexity, and the implementation of the overall processing string in real-time was demonstrated.

Paper Details

Date Published: 2 August 1999
PDF: 12 pages
Proc. SPIE 3710, Detection and Remediation Technologies for Mines and Minelike Targets IV, (2 August 1999); doi: 10.1117/12.357084
Show Author Affiliations
Tom Aridgides, Lockheed Martin Ocean, Radar & Sensor Systems (United States)
Manuel F. Fernandez, Lockheed Martin Ocean, Radar & Sensor Systems (United States)
Gerald J. Dobeck, Naval Surface Warfare Ctr. (United States)

Published in SPIE Proceedings Vol. 3710:
Detection and Remediation Technologies for Mines and Minelike Targets IV
Abinash C. Dubey; James F. Harvey; J. Thomas Broach; Regina E. Dugan, Editor(s)

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