Performance analysis of the Bayesian beamformer

Author

Lam, Chunwei Jethro ; Singer, Andrew C.

Author_Institution

Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA

Volume

2

fYear

2004

fDate

17-21 May 2004

Abstract

We present an analysis of the performance of Bayesian beamformers that are able to estimate signals from unknown source directions by balancing multiple optimal estimates according to the a posteriori probability mass function (PMF). We show that the conditional mean square error (MSE) of the Bayesian beamformer asymptotically achieves the conditional MSE of an estimator that has prior knowledge of the true direction of arrival. The convergence rate depends on both the signal-to-noise ratio (SNR) and the Kullback Leibler distance between certain probability distributions on which the Bayesian model is defined.

Keywords

Bayes methods; array signal processing; convergence of numerical methods; direction-of-arrival estimation; mean square error methods; statistical distributions; Bayesian beamformer; Kullback Leibler distance; MSE; SNR; a posteriori probability mass function; conditional mean square error; convergence rate; direction of arrival; multiple optimal estimates; performance analysis; probability distributions; signal estimation; signal-to-noise ratio; unknown source directions; Bayesian methods; Convergence; Direction of arrival estimation; Mean square error methods; Optimized production technology; Performance analysis; Sensor arrays; Signal analysis; Signal processing; Signal to noise ratio;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on

ISSN

1520-6149

Print_ISBN

0-7803-8484-9

Type

conf

DOI

10.1109/ICASSP.2004.1326228

Filename

1326228