基于遗传算法的子阵划分和子阵权值联合优化

Joint Optimization of Subarray Division and Subarray Weights Based on Genetic Algorithm

雷达中经常采取和波束在阵元级最优形成、差波束在子阵级次优形成的波束形成方式,此时差波束的子阵划分和子阵权值需要联合优化解决。文中提出了基于遗传算法的子阵划分和子阵权值联合优化方法。在子阵数量预先确定的前提下,该方法对子阵划分采用Grefenstette编码,以避免二进制编码的个体缺失或重复问题,对子阵权值则采用二进制编码,两种编码构成混合染色体用于优化迭代,并给出了遗传算法的迭代实现过程。仿真结果表明:所得到的差波束方向图主瓣形状良好,副瓣分布均匀,无明显栅瓣,达到了预期目的。

In radar the sum beam is often optimally formed at the element level,and the difference beam is suboptimally formed at the subarray level.In this case,the subarray division and subarray weights of the difference beam need to be jointly optimized.The joint optimization method of subarray division and subarray weights based on genetic algorithm is presented in this paper.On the premise that the number of subarrays is given beforehand,the Grefenstette coding is applied for the subarray division to avoid the individual deletion or duplication related to the binary coding,and the binary coding is done for the subarray weights.Both codings constitute the mixed chromosome,and the iteration process of the genetic algorithm is provided.The simulation result shows that the mainlobe shape of the optimized difference beam pattern is well,the distribution of sidelobes is even,and distinct grating lobes are not found,therefore the desired aim is achieved.