Improving the Efficiency of Natural Computing Algorithms in DOA Estimation Using a Noise Filtering Approach

Boccato, L.; Krummenauer, R.; Attux, R.; Lopes, A.

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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Improving the Efficiency of Natural Computing Algorithms in DOA Estimation Using a Noise Filtering Approach

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Author(s):	Boccato, L. ^[1] ; Krummenauer, R. ^[1] ; Attux, R. ^[1] ; Lopes, A. ^[1] Total Authors: 4
Affiliation:	^[1] Univ Campinas UNICAMP, Sch Elect & Comp Engn FEEC, BR-13083852 Sao Paulo - Brazil Total Affiliations: 1
Document type:	Journal article
Source:	CIRCUITS SYSTEMS AND SIGNAL PROCESSING; v. 32, n. 4, p. 1991-2001, AUG 2013.
Web of Science Citations:	1
Abstract
We propose a novel strategy to generate initial candidate solutions for bio-inspired algorithms applied to the direction of arrival estimation problem. The idea, which aims to improve the efficiency of the estimator, consists in using the frequency response of a well-known optimum noise reduction filter as the probability density function of the set of candidate solutions. In accordance to this approach, we also employ a modified likelihood function to reduce the estimation error. Simulation results considering an immune-inspired algorithm confirm a significant improvement of its performance and efficiency, and the new estimator reaches the conditional Cram,r-Rao lower bound. (AU)

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