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

Publication ,  Journal Article
Dasgupta, N; Runkle, P; Couchman, L; Carin, L
Published in: Signal Processing
June 1, 2001

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.

Duke Scholars

Published In

Signal Processing

DOI

ISSN

0165-1684

Publication Date

June 1, 2001

Volume

81

Issue

6

Start / End Page

1303 / 1316

Related Subject Headings

  • Networking & Telecommunications
  • 46 Information and computing sciences
  • 40 Engineering
  • 10 Technology
  • 09 Engineering
  • 08 Information and Computing Sciences
 

Citation

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Dasgupta, N., Runkle, P., Couchman, L., & Carin, L. (2001). Dual hidden Markov model for characterizing wavelet coefficients from multi-aspect scattering data. Signal Processing, 81(6), 1303–1316. https://doi.org/10.1016/S0165-1684(00)00262-0
Dasgupta, N., P. Runkle, L. Couchman, and L. Carin. “Dual hidden Markov model for characterizing wavelet coefficients from multi-aspect scattering data.” Signal Processing 81, no. 6 (June 1, 2001): 1303–16. https://doi.org/10.1016/S0165-1684(00)00262-0.
Dasgupta N, Runkle P, Couchman L, Carin L. Dual hidden Markov model for characterizing wavelet coefficients from multi-aspect scattering data. Signal Processing. 2001 Jun 1;81(6):1303–16.
Dasgupta, N., et al. “Dual hidden Markov model for characterizing wavelet coefficients from multi-aspect scattering data.” Signal Processing, vol. 81, no. 6, June 2001, pp. 1303–16. Scopus, doi:10.1016/S0165-1684(00)00262-0.
Dasgupta N, Runkle P, Couchman L, Carin L. Dual hidden Markov model for characterizing wavelet coefficients from multi-aspect scattering data. Signal Processing. 2001 Jun 1;81(6):1303–1316.
Journal cover image

Published In

Signal Processing

DOI

ISSN

0165-1684

Publication Date

June 1, 2001

Volume

81

Issue

6

Start / End Page

1303 / 1316

Related Subject Headings

  • Networking & Telecommunications
  • 46 Information and computing sciences
  • 40 Engineering
  • 10 Technology
  • 09 Engineering
  • 08 Information and Computing Sciences