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

Xijejun Liao, Paul Runkle, Lawrence Carin

Research output: Contribution to journalArticlepeer-review

120 Scopus citations

Abstract

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.
Original languageEnglish (US)
Pages (from-to)1230-1242
Number of pages13
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume38
Issue number4
DOIs
StatePublished - Oct 1 2002
Externally publishedYes

Fingerprint Dive into the research topics of 'Identification of ground targets from sequential high-range-resolution radar signatures'. Together they form a unique fingerprint.

Cite this