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Proceedings Paper

Dual hidden Markov model characterization of wavelet coefficients from multiaspect scattering data
Author(s): Nilanjan Dasgupta; Paul R. Runkle; Luise S. Couchman; Lawrence Carin
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Paper Abstract

We consider angle-dependent scattering form a general target, for which the scattered signal is a non-stationary function of the target-sensor orientation. A statistical model is presented for the wavelet coefficients of such a signal, in which the angular non-stationary is characterized by an 'outer' hidden Markov model. The statistics of the wavelet coefficients, within a state of the outer HMM, are characterized by a second, 'inner' HMM, exploiting the tree structure of the wavelet decomposition. This dual-HMM construct is demonstrated by considering multi-aspect target identification using measured acoustic scattering data.

Paper Details

Date Published: 22 August 2000
PDF: 12 pages
Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000); doi: 10.1117/12.396179
Show Author Affiliations
Nilanjan Dasgupta, Duke Univ. (United States)
Paul R. Runkle, Duke Univ. (United States)
Luise S. Couchman, Naval Research Lab. (United States)
Lawrence Carin, Duke Univ. (United States)

Published in SPIE Proceedings Vol. 4038:
Detection and Remediation Technologies for Mines and Minelike Targets V
Abinash C. Dubey; James F. Harvey; J. Thomas Broach; Regina E. Dugan, Editor(s)

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