On focusing matrices for wide-band array processing

Author

Doron, Miriam A. ; Weiss, Anthony J.

Author_Institution

RAFAEL, Haifa, Israel

Volume

40

Issue

6

fYear

1992

fDate

6/1/1992 12:00:00 AM

Firstpage

1295

Lastpage

1302

Abstract

A general class of transformation matrices for coherent signal-subspace processing is presented. These signal-subspace transformation (SST) matrices are shown to generate a sufficient statistic for maximum-likelihood bearing estimation. Two general forms for calculating SST matrices are presented, and the rotational signal-subspace (RSS) focusing matrices proposed by H. Hung and M. Kaveh (1988) are shown to be a special case of the SST matrices. An efficient procedure for computing a subset of the SST matrices, utilizing Householder transformations, is presented. The procedure reduces the computational load by a factor of 10, compared with that for the RSS matrices. The application of MUSIC to the coherently combined covariance matrix is also discussed, and Monte Carlo simulations comparing the performance of Householder SST matrices and RSS matrices are performed

Keywords

Monte Carlo methods; matrix algebra; parameter estimation; signal processing; transforms; Householder transformations; MUSIC; Monte Carlo simulations; coherent signal-subspace processing; coherently combined covariance matrix; computational load; focusing matrices; maximum-likelihood bearing estimation; transformation matrices; wide-band array processing; Array signal processing; Covariance matrix; Direction of arrival estimation; Maximum likelihood detection; Maximum likelihood estimation; Multiple signal classification; Narrowband; Signal processing; Statistics; Wideband;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.139236

Filename

139236