Improving the threshold performance of maximum likelihood estimation of direction of arrival

Author(s)

Krummenauer, R. ^{[1, 2]} ; Cazarotto, M. ^[1] ; Lopes, A. ^[1] ; Larzabal, P. ^[3] ; Forster, P. ^[4]

Affiliation

^[1] Univ Estadual Campinas, UNICAMP, Dept Comunicacoes, FEEC 6101, BR-13083852 Campinas, SP - Brazil

^[2] Univ Estadual Campinas, UNICAMP, Lab DSPCOM, FEEC 6101, BR-13083852 Campinas, SP - Brazil

^[3] CNRS, ENS CACHAN, Lab SATIE, F-94235 Cachan - France

^[4] Univ Paris 10, GEA, F-92410 Ville Davray - France

• Document type: Journal article
• Source: Signal Processing; v. 90, n. 5, p. 1582-1590, MAY 2010.
• Web of Science Citations: 10

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. (AU)

• FAPESP's process: 03/09858-6 - Linearity in signals, circuits and systems
• Grantee: Pedro Luis Dias Peres
• Support Opportunities: Research Projects - Thematic Grants