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

Autor(es)

Boccato, L. ^[1] ; Krummenauer, R. ^[1] ; Attux, R. ^[1] ; Lopes, A. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Campinas UNICAMP, Sch Elect & Comp Engn FEEC, BR-13083852 Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: CIRCUITS SYSTEMS AND SIGNAL PROCESSING; v. 32, n. 4, p. 1991-2001, AUG 2013.
• Citações Web of Science: 1

Resumo

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)

• Processo FAPESP: 10/51027-8 - Novas propostas e aplicações de redes neurais com estados de eco
• Beneficiário: Levy Boccato
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 08/56937-2 - Aplicacao de computacao natural no processamento de sinais por arranjo de sensores
• Beneficiário: Levy Boccato
• Modalidade de apoio: Bolsas no Brasil - Mestrado