3-D Near Field Source Localization by using Hybrid Genetic Algorithm

In this study, a method based on hybrid Genetic Algorithm is used to jointly estimate 3-D (range, amplitude, elevation angle) parameters of near field sources arriving on uniform linear array. In this approach, Genetic Algorithm is hybridized with pattern Search. In this hybridization, Genetic Algorithm acts as a global search optimizer while Pattern Search is used as a rapid local search optimizer. The performance of Genetic algorithm and pattern search alone is also evaluated. The fitness function used in this study is based on Mean Square Error. This fitness function acted well even in the presence of low signal to noise ratio and requires only single snap-shot to achieve the goal. The validity and efficiency of the proposed approach is checked through a large number of Monte Carlo Simulations.

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