Classification of distant targets situated near channel bottoms

Hongwei Liu, Paul Runkle, Lawrence Carin, Timothy Yoder, Thomas Giddings, Luise Couchman, Joseph Bucaro

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Identification algorithms are considered for a class of targets situated near the bottom of a water channel. It is assumed that the target-sensor distance relative to the channel depth is such that a ray-based representation of the scattered fields is appropriate (vis-à-vis a modal representation). Two approaches are considered for processing the scattered fields. In one algorithm a deconvolution is performed to remove the channel response, and thereby recover the free-field target scattered signature. In this case the classifier is trained based on free-field data. In the second approach the array receiver is employed to point the sensor in particular directions, and the beam-formed signal is used directly in the subsequent classifier. In this case the classifier must be trained based on. in-channel data. Multiple scattered signals are measured, from a sequence of target-sensor orientations, with the waveforms classified via a hidden Markov model. Example results are presented for scattering data simulated via the finite-element method and coupled to a normal-mode waveguide modal, for elastic targets situated in a water channel. © 2004 Acoustical Society of America.
Original languageEnglish (US)
Pages (from-to)1185-1197
Number of pages13
JournalJournal of the Acoustical Society of America
Volume115
Issue number3
DOIs
StatePublished - Mar 1 2004
Externally publishedYes

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