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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 results are presented for the ten-target MSTAR data set.
Published in:
Aerospace and Electronic Systems, IEEE Transactions on
(Volume:38
,
Issue:
4
)
Date of Publication: Oct 2002
- Page(s):
- 1230 - 1242
- ISSN :
- 0018-9251
- INSPEC Accession Number:
- 7497148
- Digital Object Identifier :
- 10.1109/TAES.2002.1145746
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 January 2003
- Issue Date :
- Oct 2002
- Sponsored by :
- Aerospace & Electronic Systems Society
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