Dual hidden Markov model characterization of wavelet coefficients from multiaspect scattering data

Nilanjan Dasgupta; Paul R. Runkle; Luise S. Couchman; Lawrence Carin

doi:10.1117/12.396179

22 August 2000 Dual hidden Markov model characterization of wavelet coefficients from multiaspect scattering data

Nilanjan Dasgupta, Paul R. Runkle, Luise S. Couchman, Lawrence Carin

Proceedings Volume 4038, Detection and Remediation Technologies for Mines and Minelike Targets V; (2000) https://doi.org/10.1117/12.396179
Event: AeroSense 2000, 2000, Orlando, FL, United States

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.

Citation Download Citation

Nilanjan Dasgupta, Paul R. Runkle, Luise S. Couchman, and Lawrence Carin "Dual hidden Markov model characterization of wavelet coefficients from multiaspect scattering data", Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000); https://doi.org/10.1117/12.396179

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