Performance analysis of the bayesian beamformer

Chunwei Jethro Lam; Andrew C. Singer

Performance analysis of the bayesian beamformer

Chunwei Jethro Lam
, Andrew C. Singer

Office of the Dean of the College of Engineering and Applied Sciences

University of Illinois at Urbana-Champaign

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

We present an analysis of the performance of Bayesian beamformers that are able to estimate signals from unknowns 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.

Original language	English
Pages (from-to)	II197-II200
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2
State	Published - 2004
Event	Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada Duration: May 17 2004 → May 21 2004

Cite this

@article{37684c9062e34aa39c5c8aa9c79af551,

title = "Performance analysis of the bayesian beamformer",

abstract = "We present an analysis of the performance of Bayesian beamformers that are able to estimate signals from unknowns 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.",

author = "Lam, \{Chunwei Jethro\} and Singer, \{Andrew C.\}",

year = "2004",

language = "English",

volume = "2",

pages = "II197--II200",

journal = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

issn = "0736-7791",

note = "Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing ; Conference date: 17-05-2004 Through 21-05-2004",

}

TY - JOUR

T1 - Performance analysis of the bayesian beamformer

AU - Lam, Chunwei Jethro

AU - Singer, Andrew C.

PY - 2004

Y1 - 2004

N2 - We present an analysis of the performance of Bayesian beamformers that are able to estimate signals from unknowns 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.

AB - We present an analysis of the performance of Bayesian beamformers that are able to estimate signals from unknowns 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.

UR - https://www.scopus.com/pages/publications/4644297999

M3 - Conference article

AN - SCOPUS:4644297999

SN - 0736-7791

VL - 2

SP - II197-II200

JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing

Y2 - 17 May 2004 through 21 May 2004

ER -

Performance analysis of the bayesian beamformer

Abstract

Other files and links

Fingerprint

Cite this