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

Author

Liao, Xuejun ; Runkle, Paul ; Carin, Lawrence

Author_Institution

Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC, USA

Volume

38

Issue

4

fYear

2002

fDate

10/1/2002 12:00:00 AM

Firstpage

1230

Lastpage

1242

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 results are presented for the ten-target MSTAR data set.

Keywords

hidden Markov models; radar resolution; radar target recognition; MSTAR classification; RELAX algorithm; expectation-maximization training algorithm; ground target identification; hidden Markov model; sequential high-range-resolution radar signature; Application software; Data mining; Hidden Markov models; High performance computing; Microelectronics; Object detection; Scattering; Signal resolution; Statistics; Synthetic aperture radar;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2002.1145746

Filename

1145746