Hidden Markov models for multiaspect target classification


Journal Article

This correspondence presents a new approach for target identification, in which we fuse scattering data from multiple target-sensor orientations. The multiaspect data is processed via hidden Markov model (HMM) classifiers, buttressed by physics-based feature extraction. This approach explicitly accounts for the fact that the target-sensor orientation is generally unknown or 'hidden'. Discrimination results are presented for measured scattering data.

Full Text

Duke Authors

Cited Authors

  • Runkle, PR; Bharadwaj, PK; Couchman, L; Carin, L

Published Date

  • January 1, 1999

Published In

Volume / Issue

  • 47 / 7

Start / End Page

  • 2035 - 2040

International Standard Serial Number (ISSN)

  • 1053-587X

Digital Object Identifier (DOI)

  • 10.1109/78.771050

Citation Source

  • Scopus