The robust covariation-based MUSIC (ROC-MUSIC) algorithm for bearing estimation in impulsive noise environments

Author

Tsakalides, Panagiotis ; Nikias, Chrysostomos L.

Author_Institution

Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA

Volume

44

Issue

7

fYear

1996

fDate

7/1/1996 12:00:00 AM

Firstpage

1623

Lastpage

1633

Abstract

This paper presents a new subspace-based method for bearing estimation in the presence of impulsive noise which can be modeled as a complex symmetric alpha-stable (SαS) process. We define the covariation matrix of the array sensor outputs and show that eigendecomposition-based methods, such as the MUSIC algorithm, can be applied to the sample covariation matrix to extract the bearing information from the measurements. A consistent estimator for the marginals of the covariation matrix is presented and its asymptotic performance is studied. The improved performance of the proposed source localization method in the presence of a wide range of impulsive noise environments is demonstrated via Monte Carlo experiments

Keywords

Monte Carlo methods; covariance matrices; direction-of-arrival estimation; eigenvalues and eigenfunctions; noise; Monte Carlo experiments; ROC-MUSIC algorithm; array sensor outputs; asymptotic performance; bearing estimation; bearing information; complex symmetric alpha-stable process; eigendecomposition based methods; impulsive noise environments; marginals; measurements; robust covariation-based MUSIC algorithm; sample covariation matrix; source localization method; subspace based method; Array signal processing; Computational efficiency; Direction of arrival estimation; Gaussian processes; Multiple signal classification; Noise robustness; Random processes; Sensor arrays; Symmetric matrices; Working environment noise;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.510611

Filename

510611