Sidelobe reduction on conformal array using genetic algorithm
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Fractal geometry has been applied to numerous designs of antenna arrays with the improvement in sidelobe reduction and broadband coverage. Moreover, the concept of fractal gives the self-similar characteristic and space-filling capability. Various fractal geometries have been observed such as Koch curves, Sierpinski curves, Peano curves, and so on which are widely employed in many applications. In this study, the objective is to analyze the fractal array behavior in sidelobe reduction when conformed to various surfaces. We use Genetic algorithm (GA) to determine the sidelobe level through the ...
Fractal geometry has been applied to numerous designs of antenna arrays with the improvement in sidelobe reduction and broadband coverage. Moreover, the concept of fractal gives the self-similar characteristic and space-filling capability. Various fractal geometries have been observed such as Koch curves, Sierpinski curves, Peano curves, and so on which are widely employed in many applications. In this study, the objective is to analyze the fractal array behavior in sidelobe reduction when conformed to various surfaces. We use Genetic algorithm (GA) to determine the sidelobe level through the vast space of solution. GA is an optimization method based on the theory of natural selection which is suitable for a large number of parameters like excitation on each element of fractal arrays.
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