Thinned array optimization by means of M-cGA

The synthesis of thinned arrays by means of optimization is presented in this paper using compact genetic algorithm (cGA). The optimization algorithm implements a probability vector to represent the population, which is suitable to apply to thinned array problem. Moreover, by introducing some modifications to the original cGA, the peak side-lobe level (PSLL) of the thinned array is well controlled. The effectiveness of the method is demonstrated by applying to various 200-element linear arrays and compared to literature reported results.

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