Performance of spatial smoothing algorithms for correlated sources

Author

Thompson, John S. ; Grant, Peter M. ; Mulgrew, Bernard

Author_Institution

Dept. of Electr. Eng., Edinburgh Univ., UK

Volume

44

Issue

4

fYear

1996

fDate

4/1/1996 12:00:00 AM

Firstpage

1040

Lastpage

1046

Abstract

The problem of identifying the angles of arrival of a set of plane waves impinging on a narrowband array of sensors and related spectral analysis problems have been addressed with a large number of algorithms. One of the most popular techniques is the multiple signal classification (MUSIC). The major shortcoming of the MUSIC algorithm is that it performs poorly when the sources are highly correlated. Fortunately, two algorithms exist to overcome this problem-spatial smoothing (SS) and forward-backward spatial smoothing (FBSS). The performance of the SS technique depends on signal bearings and spatial separation. For the same smoothing, FBSS can offer improved performance, but this depends on the signal phases. Numerical results for the variance of the algorithms are given to illustrate the points made

Keywords

correlation theory; direction-of-arrival estimation; smoothing methods; spectral analysis; DOA estimation; MUSIC; angles of arrival; correlated sources; forward-backward spatial smoothing; multiple signal classification; narrowband array of sensors; performance; plane waves; signal bearings; spatial separation; spatial smoothing algorithms; spectral analysis; variance; Analysis of variance; Covariance matrix; Direction of arrival estimation; Equations; Multiple signal classification; Sensor arrays; Signal processing; Signal processing algorithms; Signal resolution; Smoothing methods;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.492567

Filename

492567