A low-complexity implementation of adaptive Wiener filters

Author

Goldstein, J.Scott ; Reed, Irving S. ; Schar, Louis L. ; Tague, John A.

Author_Institution

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

Volume

1

fYear

1997

fDate

2-5 Nov. 1997

Firstpage

770

Abstract

Wiener filters of arbitrary order can be implemented by a nested structure of one-dimensional filters. The multistage processor is simple to implement, and covariance matrix estimation and inversion are not required to calculate the filter weights. The nested structure provides a new framework for designing and implementing reduced complexity filters. When applied to a typical array processing problem, it provides close to optimum performance, even when its degrees of freedom are less than the rank of the interference subspace.

Keywords

Wiener filters; adaptive filters; array signal processing; band-pass filters; computational complexity; digital filters; direction-of-arrival estimation; filtering theory; interference (signal); adaptive Wiener filters; array processing; degrees of freedom; filter weights; filterbanks; interference subspace rank; low-complexity implementation; multistage processor; nested structure; one-dimensional filters; optimum performance; reduced complexity filters; Array signal processing; Covariance matrix; Eigenvalues and eigenfunctions; Equations; Interference; Matrix decomposition; Radar; Sensor arrays; Sonar; Wiener filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-8186-8316-3

Type

conf

DOI

10.1109/ACSSC.1997.680548

Filename

680548