Identification of ground targets from sequential HRR radar signatures

X. Liao, P. Runkle, Y. Jiao, L. Carin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations


An approach to identifying ground targets from sequential high-range-resolution (HRR) radar signatures is presented. A hidden Markov model (HMM) is employed to model the sequential information contained in multi-aspect target signatures. Dominant range-amplitude features are extracted via RELAX for dimension reduction. A new distance measure is incorporated into the HMM to allow a direct matching operation in the feature domain without requiring interpolation. The approach is applied to the dataset of ten MSTAR targets and is shown to yield an average identification rate of 90.3% using sequential information from 6 degree angular spans.
Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Number of pages4
StatePublished - Sep 26 2001
Externally publishedYes

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Generated from Scopus record by KAUST IRTS on 2021-02-09


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