Dual hidden Markov model characterization of wavelet coefficients from multi-aspect scattering data

Nilanjan Dasgupta, Paul Runkle, Luise Couchman, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We consider angle-dependent scattering (electromagnetic or acoustic) from 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 (HMMo). The statistics of the wavelet coefficients, within a state of the outer HMM, are characterized by a second, 'inner' HMM (HMMi), 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.
Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation EngineersBellingham
Pages954-965
Number of pages12
DOIs
StatePublished - Jan 1 2000
Externally publishedYes

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