Dispersion-invariant features for classification of objects from their acoustic backscatter in a range-dependent channel

Vikram Gomatam; Patrick Loughlin

doi:10.1117/12.918912

2 May 2012 Dispersion-invariant features for classification of objects from their acoustic backscatter in a range-dependent channel

Vikram Gomatam, Patrick Loughlin

Author Affiliations +

Proceedings Volume 8391, Automatic Target Recognition XXII; 83910D (2012) https://doi.org/10.1117/12.918912
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

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.

Citation Download Citation

Vikram Gomatam and Patrick Loughlin "Dispersion-invariant features for classification of objects from their acoustic backscatter in a range-dependent channel", Proc. SPIE 8391, Automatic Target Recognition XXII, 83910D (2 May 2012); https://doi.org/10.1117/12.918912

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