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Proceedings Paper

Rapid surveying of buried targets by hybrid seafloor image and biomimetic signal classification
Author(s): Daniel D. Sternlicht; R. David Dikeman; David W. Lemonds; Marc Ericksen; Steven G. Schock
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Paper Abstract

Acoustic detection and classification of buried mines presents a challenging and, as of yet, unsolved object recognition problem. Techniques for detecting and classifying mine-like targets in backscatter images created with broadband sonars are starting to yield promising results. These images represent energy vs. time mappings of target echoes; however, further information on potential targets can be extracted from the spectral and temporal content of these broadband signals. An approach to classifying the time-frequency characteristics of target echoes measured with a 3D, 5-23 kHz, forward/aft sweeping, buried object imaging system is described. Matched spatial filters are applied to backscatter images representing horizontal seafloor slices. Detection outputs are used to identify beams and ranges for candidate targets. Time- spectral features are then extracted from the appropriate time-series component, and input to an artificial neural network trained to identify mine-like objects. Fusion of image and signal classification algorithms applied to these data is expected to result in rapid identification of buried targets and a reduction in false alarm rates.

Paper Details

Date Published: 18 October 2001
PDF: 7 pages
Proc. SPIE 4394, Detection and Remediation Technologies for Mines and Minelike Targets VI, (18 October 2001); doi: 10.1117/12.445446
Show Author Affiliations
Daniel D. Sternlicht, ORINCON Corp. (United States)
R. David Dikeman, ORINCON Corp. (United States)
David W. Lemonds, ORINCON Corp. (United States)
Marc Ericksen, Sea Engineering Inc. (United States)
Steven G. Schock, Florida Atlantic Univ. (United States)

Published in SPIE Proceedings Vol. 4394:
Detection and Remediation Technologies for Mines and Minelike Targets VI
Abinash C. Dubey; James F. Harvey; J. Thomas Broach; Vivian George, Editor(s)

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