Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/69296
Type: Artigo de periódico
Title: Improving the threshold performance of maximum likelihood estimation of direction of arrival
Author: Krummenauer, R
Cazarotto, M
Lopes, A
Larzabal, P
Forster, P
Abstract: We propose to improve the performance of some direction of arrival (DOA) estimators using array of sensors. We consider those maximum likelihood (ML) estimators that generate some DOA candidates and select one of them through an ML criterion. Our proposal modifies the candidate selection process substituting the traditional sample covariance matrix by a new one computed after filtering the received data with an optimum noise reduction filter. Simulation results indicate an improvement of the performance at low signal-to-noise ratios (SNR) and a considerable reduction of the threshold SNR. The computation of the new selection cost function implies in a small increase in the overall computational effort. (C) 2009 Elsevier B.V. All rights reserved.
Subject: Array signal processing
Direction of arrival estimation
Maximum likelihood estimation
Optimum filtering
Country: Holanda
Editor: Elsevier Science Bv
Rights: fechado
Identifier DOI: 10.1016/j.sigpro.2009.10.028
Date Issue: 2010
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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