Identification of ground targets from sequential high-range-resolution radar signatures

Published

Journal Article

An approach to identifying targets from sequential high-range-resolution (HRR) radar signatures is presented. In particular, a hidden Markov model (HMM) is employed to characterize the sequential information contained in multiaspect HRR target signatures. Features from each of the HRR waveforms are extracted via the RELAX algorithm. The statistical models used for the HMM states are formulated for application to RELAX features, and the expectation-maximization (EM) training algorithm is augmented appropriately. Example classification resulte are presented for the ten-target MSTAR data set.

Full Text

Duke Authors

Cited Authors

  • Liao, X; Runkle, P; Carin, L

Published Date

  • October 1, 2002

Published In

Volume / Issue

  • 38 / 4

Start / End Page

  • 1230 - 1242

International Standard Serial Number (ISSN)

  • 0018-9251

Digital Object Identifier (DOI)

  • 10.1109/TAES.2002.1145746

Citation Source

  • Scopus