Asymptotic properties of the algebraic constant modulus algorithm

Author

Van der Veen, Alle-Jan

Author_Institution

Dept. of Electr. Eng., Delft Univ. of Technol., Netherlands

Volume

49

Issue

8

fYear

2001

fDate

8/1/2001 12:00:00 AM

Firstpage

1796

Lastpage

1807

Abstract

The algebraic constant modulus algorithm (ACMA) is a noniterative blind source separation algorithm. It computes jointly beamforming vectors for all constant modulus sources as the solution of a joint diagonalization problem. We analyze its asymptotic properties and show that (unlike CMA) it converges to the Wiener beamformer when the number of samples or the signal-to-noise ratio (SNR) goes to infinity. We also sketch its connection to the related JADE algorithm and derive a version of ACMA that converges to a zero-forcing beamformer. This gives improved performance in applications that use the estimated mixing matrix, such as in direction finding

Keywords

array signal processing; convergence of numerical methods; direction-of-arrival estimation; matrix algebra; JADE algorithm; SNR; Wiener beamformer; algebraic constant modulus algorithm; asymptotic properties; constant modulus sources; convergence; direction finding; estimated mixing matrix; joint diagonalization problem; jointly beamforming vectors; noniterative blind source separation algorithm; samples; signal-to-noise ratio; zero-forcing beamformer; Adaptive equalizers; Adaptive signal processing; Array signal processing; Blind equalizers; Blind source separation; Cost function; H infinity control; Signal analysis; Signal processing algorithms; Signal to noise ratio;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.934150

Filename

934150