Spatial and spectral parameter estimation of multiple source signals

Mordechai Segal, Ehud Weinstein

Research output: Contribution to journalConference articlepeer-review

Abstract

The authors propose a computationally efficient scheme for estimating the spatial (location) and spectral parameters of multiple-source signals using passive array data. The source signals are modeled as possibly correlated narrowband/wideband Gaussian random processes. The authors also allow sensor-to-sensor noise correlation. The proposed algorithm is optimal in the sense that it converges monotonically to the maximum-likelihood (ML) estimates (or, at least, to a stationary point of the likelihood function) of the unknown spatial and spectral parameters.

Original languageEnglish
Pages (from-to)2665-2668
Number of pages4
JournalProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Volume4
StatePublished - 1989
Event1989 International Conference on Acoustics, Speech, and Signal Processing - Glasgow, Scotland
Duration: 23 May 198926 May 1989

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