Accurate direction-of-arrival estimation of multiple sources using a genetic approach

M. Li, Yi-Long Lu

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

In this paper, we present an accurate direction-of-arrival (DOA) estimation method, which is based on the maximum likelihood (ML) principle and implemented using a modified and refined genetic algorithm (GA). With the newly introduced features—intelligent initialization and the emperor-selective (EMS) mating scheme, carefully selected crossover and mutation operators and fine-tuned parameters such as the population size, the probability of crossover and mutation etc., the GA-ML estimator achieves fast global convergence. A GA operator and parameter standard is suggested for this application, which is independent of the source and array configurations except the number of sources. Simulation results demonstrate that in general scenarios, the proposed estimator is the most efficient in computation and its statistical performance is the best among all popular ML-based DOA estimation methods.
Original languageEnglish
Pages (from-to)343-353
Number of pages11
JournalWireless Communications and Mobile Computing
Volume5
Issue number3
Early online date23 Aug 2004
DOIs
Publication statusPublished - May 2005

Keywords

  • array processing
  • direction finding
  • genetic algorithms

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