Time-frequency MUSIC

Author

Belouchrani, Adel ; Amin, Moeness G.

Author_Institution

Dept. of Electr. & Comput. Eng., Villanova Univ., PA, USA

Volume

6

Issue

5

fYear

1999

fDate

5/1/1999 12:00:00 AM

Firstpage

109

Lastpage

110

Abstract

A new method for the estimation of the signal subspace and noise subspace based on time-frequency signal representations is introduced. The proposed approach consists of the joint block-diagonalization (JBD) of a set of spatial time-frequency distribution matrices. Once the signal and noise subspaces are estimated, any subspace based approach, including the multiple signal classification (MUSIC) algorithm, can be applied for direction of arrival (DOA) estimation. Performance of the proposed time-frequency MUSIC (TF-MUSIC) for an impinging chirp signal using three different kernels is numerically evaluated.

Keywords

array signal processing; direction-of-arrival estimation; matrix algebra; signal classification; signal representation; time-frequency analysis; DOA estimation; MUSIC algorithm; direction of arrival estimation; impinging chirp signal; joint block-diagonalization; multiple signal classification; noise subspace estimation; signal subspace estimation; spatial time-frequency distribution matrices; time-frequency kernels; time-frequency signal representation; Associate members; Blind source separation; Classification algorithms; Direction of arrival estimation; Kernel; Multiple signal classification; Sensor arrays; Signal processing algorithms; Signal representations; Time frequency analysis;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/97.755429

Filename

755429