Dual hidden Markov model for characterizing wavelet coefficients from multi-aspect scattering data

Published

Journal Article

Angle-dependent scattering (electromagnetic or acoustic) is considered 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-stationarity 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" 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. © 2001 Elsevier Science B.V.

Full Text

Duke Authors

Cited Authors

  • Dasgupta, N; Runkle, P; Couchman, L; Carin, L

Published Date

  • June 1, 2001

Published In

Volume / Issue

  • 81 / 6

Start / End Page

  • 1303 - 1316

International Standard Serial Number (ISSN)

  • 0165-1684

Digital Object Identifier (DOI)

  • 10.1016/S0165-1684(00)00262-0

Citation Source

  • Scopus