Maximum likelihood source localization using the EM algorithm to incorporate prior parameter distributions

Author

Perry, Richard ; Buckley, Kevin

Author_Institution

Dept. of Electr. & Comput. Eng., Villanova Univ., PA, USA

fYear

2000

fDate

2000

Firstpage

351

Lastpage

355

Abstract

We introduce a new algorithm for the estimation of source location parameters from array data given prior distributions on unknown nuisance source signal parameters. The conditional maximum-likelihood (CML) formulation is employed, and ML estimation is obtained by marginalizing over the nuisance parameters. In general, direct solution of this marginalization ML problem is intractable. We introduce an expectation-maximization (EM) algorithm solution, which is applicable to any prior distribution

Keywords

AWGN; array signal processing; direction-of-arrival estimation; maximum likelihood estimation; optimisation; probability; AWGN; EM algorithm; ML estimation; amplitude probability distribution functions; array data; conditional maximum-likelihood formulation; direct solution; expectation-maximization algorithm; general joint PDF; marginalization ML problem; maximum likelihood source localization; nuisance source signal parameters; prior parameter distributions; random signal amplitudes; source location parameters; source signal parameters; Acoustic applications; Biomedical acoustics; Biomedical engineering; Maximum likelihood estimation; Parameter estimation; Position measurement; Radar applications; Sensor arrays; Signal processing algorithms; Sonar applications;

fLanguage

English

Publisher

ieee

Conference_Titel

Sensor Array and Multichannel Signal Processing Workshop. 2000. Proceedings of the 2000 IEEE

Conference_Location

Cambridge, MA

Print_ISBN

0-7803-6339-6

Type

conf

DOI

10.1109/SAM.2000.878028

Filename

878028