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|Type:||Artigo de periódico|
|Title:||Improving the Efficiency of Natural Computing Algorithms in DOA Estimation Using a Noise Filtering Approach|
|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.|
|Subject:||Direction of arrival estimation|
Maximum likelihood estimator
|Appears in Collections:||Artigos e Materiais de Revistas Científicas - Unicamp|
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