Synthesis of Sparse Planar Arrays Using Modified Real Genetic Algorithm
Synthesis of Sparse Planar Arrays Using Modified Real Genetic Algorithm
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DOI：
10.1109/tap.2007.898240
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发表时间：
2007-04
影响因子：
5.7
通讯作者：
Kesong Chen;Xiaohua Yun;Zishu He;Chunlin Han
中科院分区：
文献类型：
--
作者：
Kesong Chen;Xiaohua Yun;Zishu He;Chunlin Han
在阵列设计中，稀疏阵列元素的位置是实现最小峰值旁瓣电平 (SLL) 的最佳性能的重要考虑因素。针对矩形边界稀疏平面阵列的阵元位置优化问题，提出一种基于染色体重置的改进实数遗传算法（MGA）。这里的多重优化约束包括元件数量、孔径和最小元件间距。 MGA通过将元素之间的空间从实际距离简化为切比雪夫距离，通过个体的间接描述来搜索更小的解空间，并通过两个新颖的遗传算子避免优化过程中的不可行解。最后，本文的仿真结果证实了该方法的高效性和鲁棒性
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