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Synthesis of Sparse Planar Arrays Using Modified Real Genetic Algorithm

机译:用改进的实数遗传算法合成稀疏平面阵列。

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In array design, the positions of sparse array elements is an important concern for optimal performance in terms of its ability to achieve minimum peak sidelobe level (SLL). This paper proposes a modified real genetic algorithm (MGA) based on resetting of chromosome for the element position optimization of sparse planar arrays with rectangular boundary. And here the multiple optimization constraints include the number of elements, the aperture and the minimum element spacing. By simplifying the space between the elements from the actual distance to Chebychev distance, the MGA searches a smaller solution space by means of indirect description of individual, and it can avoid infeasible solution during the optimization process by two novel genetic operators. Finally, the simulation results confirming the great efficiency and the robustness of the proposed method are shown in this paper.
机译:在阵列设计中,稀疏阵列元素的位置就其实现最小峰值旁瓣电平(SLL)的能力而言,是优化性能的重要考虑因素。提出了一种基于染色体重设的改进的遗传算法,用于稀疏矩形边界平面阵列的元素位置优化。在这里,多个优化约束包括元素数量,孔径和最小元素间距。通过简化元素之间的距离(从实际距离到切比雪夫距离),MGA通过对个体的间接描述来搜索较小的解空间,并且可以避免在优化过程中由两个新颖的遗传算子产生不可行的解。最后,仿真结果证实了该方法的高效率和鲁棒性。

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