Identification of ground targets from sequential HRR radar signatures

Author

Liao, Xuejun ; Runkle, Paul ; Jiao, Yan ; Carin, Lawrence

Author_Institution

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

Volume

5

fYear

2001

fDate

2001

Firstpage

2897

Abstract

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

Keywords

airborne radar; feature extraction; hidden Markov models; radar resolution; radar target recognition; HHM; MSTAR targets; RELAX; airborne radar; average identification rate; dimension reduction; distance measure; feature domain matching; ground targets identification; hidden Markov model; high-range-resolution radar; multi-aspect target signatures; range-amplitude features extraction; sequential HRR radar signatures; Acoustic scattering; Airborne radar; Data mining; Feature extraction; Hidden Markov models; Image resolution; Interpolation; Libraries; Radar imaging; Radar scattering;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on

Conference_Location

Salt Lake City, UT

ISSN

1520-6149

Print_ISBN

0-7803-7041-4

Type

conf

DOI

10.1109/ICASSP.2001.940252

Filename

940252