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Proceedings Paper

Dispersion-invariant features for classification of objects from their acoustic backscatter in a range-dependent channel
Author(s): Vikram Gomatam; Patrick Loughlin
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Paper Abstract

We have previously developed a feature extraction process for propagation-invariant classification of a target from its propagated sonar backscatter. The features are invariant to the frequency dependent propagation effects of absorption and dispersion, for range-independent channels. Simulations have shown that these features lose their effectiveness when applied to waves propagating in a range-dependent environment. In this paper we extend our previous approach to obtain invariant features for classification in range-dependent environments. Numerical simulations are presented for the classification of two shells from their acoustic backscatter propagating in an ideal wedge.

Paper Details

Date Published: 3 May 2012
PDF: 8 pages
Proc. SPIE 8391, Automatic Target Recognition XXII, 83910D (3 May 2012); doi: 10.1117/12.918912
Show Author Affiliations
Vikram Gomatam, Univ. of Pittsburgh (United States)
Patrick Loughlin, Univ. of Pittsburgh (United States)


Published in SPIE Proceedings Vol. 8391:
Automatic Target Recognition XXII
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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