Time-reversal imaging for classification of submerged elastic targets via Gibbs sampling and the Relevance Vector Machine.

Published

Journal Article

Time-reversal imaging (TRI) is analogous to matched-field processing, although TRI is typically very wideband and is appropriate for subsequent target classification (in addition to localization). Time-reversal techniques, as applied to acoustic target classification, are highly sensitive to channel mismatch. Hence, it is crucial to estimate the channel parameters before time-reversal imaging is performed. The channel-parameter statistics are estimated here by applying a geoacoustic inversion technique based on Gibbs sampling. The maximum a posteriori (MAP) estimate of the channel parameters are then used to perform time-reversal imaging. Time-reversal implementation requires a fast forward model, implemented here by a normal-mode framework. In addition to imaging, extraction of features from the time-reversed images is explored, with these applied to subsequent target classification. The classification of time-reversed signatures is performed by the relevance vector machine (RVM). The efficacy of the technique is analyzed on simulated in-channel data generated by a free-field finite element method (FEM) code, in conjunction with a channel propagation model, wherein the final classification performance is demonstrated to be relatively insensitive to the associated channel parameters. The underlying theory of Gibbs sampling and TRI are presented along with the feature extraction and target classification via the RVM.

Full Text

Duke Authors

Cited Authors

  • Dasgupta, N; Carin, L

Published Date

  • April 2005

Published In

Volume / Issue

  • 117 / 4 Pt 1

Start / End Page

  • 1999 - 2011

PubMed ID

  • 15898643

Pubmed Central ID

  • 15898643

Electronic International Standard Serial Number (EISSN)

  • 1520-8524

International Standard Serial Number (ISSN)

  • 0001-4966

Digital Object Identifier (DOI)

  • 10.1121/1.1862592

Language

  • eng