The ESPRIT and MUSIC algorithms using the covariance matrix

Author

McGarrity, J.S. ; Soraghan, J.J. ; Durrani, T.S. ; Mayrargue, S.

Author_Institution

Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow, UK

fYear

1991

fDate

14-17 Apr 1991

Firstpage

3285

Abstract

A computationally efficient algorithm for direction finding is described. The sample covariance matrix is averaged into d column vectors, where d is the known number of sources. These column vectors are used as a basis for the signal subspace. They can be used directly for the two subspace estimates in the ESPRIT algorithm or they can be used to construct a projection matrix for use with the MUSIC algorithm. For low signal-noise-ratio conditions, a subtraction process is used to remove the diagonal noise terms from the covariance matrix and as a result a shorter search vector is used in the MUSIC algorithm

Keywords

matrix algebra; radio direction-finding; signal detection; signal processing; ESPRIT algorithm; MUSIC algorithm; SNR; column vectors; direction finding; projection matrix; sample covariance matrix; search vector; signal subspace; signal-noise-ratio; subspace estimates; subtraction process; Bismuth; Covariance matrix; Equations; Frequency; Gaussian noise; Multiple signal classification; Narrowband; Sensor arrays; Signal processing algorithms; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on

Conference_Location

Toronto, Ont.

ISSN

1520-6149

Print_ISBN

0-7803-0003-3

Type

conf

DOI

10.1109/ICASSP.1991.150155

Filename

150155