基于遗传算法的稀疏直线阵列方向图特性研究

Research into Pattern Characteristics of Sparse Linear Array Based on Genetic Algorithm

针对直线阵列天线稀疏优化中的遗传算法进行研究,给出了一种稀疏直线阵列的优化模型,介绍了遗传算法的理论,通过算法仿真,对稀疏直线阵列的方向图特性进行研究。以方向图最大副瓣电平为适应度函数,得出结论:在稀疏阵列中阵元分布呈中心聚集态势,稀疏率、种群大小和约束条件等,均会对稀疏后阵列方向图特性产生影响;遗传算法适用于稀疏优化,其种群数量的选择应综合考虑。

This article studies the genetic algorithm in the sparse optimization of linear array antennas,gives an optimization model of sparse linear arrays,introduces the theory of genetic algorithm,and studies the pattern characteristics of sparse linear arrays through algorithm simulation.Taking the maximum sidelobe level of the pattern as the fitness function,it is concluded that the distribution of array elements in the sparse array shows a central aggregation situation,and the sparse rate,population size and constraint conditions will all affect the characteristics of the pattern in the sparse array.Genetic algorithm is suitable for sparse optimization,and the selection of the number of its population should be considered comprehensively.