On the inflation method in adaptive noise-subspace estimator

Author

Ching-Tai Chiang ; Yuan-Hwang Chen

Author_Institution

Dept. of Electron. Eng., Nan-Tai Inst. of Technol., Tainan

Volume

47

Issue

4

fYear

1999

fDate

4/1/1999 12:00:00 AM

Firstpage

1125

Lastpage

1129

Abstract

It is shown that Yang and Kaveh´s (1987, 1988) inflation method is not necessary to accomplish an adaptive noise-subspace estimator. Without the inflation method, an alternative noise-subspace estimator, involving less computation and simpler parallel implementation, is developed. We also prove that if the initial noise-subspace basis consists of a set of mutually orthonormal vectors, the proposed estimator has a better performance than that with the inflation method both in the mean sense and in the mean-square sense. Computer simulations are provided to substantiate the superiority of the estimator without the inflation method

Keywords

adaptive estimation; adaptive signal processing; array signal processing; mean square error methods; noise; adaptive noise-subspace estimator; computer simulations; inflation method; linear sensor array; mean sense; mean-square sense; mutually orthonormal vectors; noise-subspace basis; parallel implementation; Computational modeling; Computer simulation; Concurrent computing; Convergence; Councils; Covariance matrix; Eigenvalues and eigenfunctions; Noise reduction; Subspace constraints; Vectors;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.752609

Filename

752609