基于NLSM+IWO的非对称方向图唯相位优化

摘要

An improved nonlinear least-square method is presented in this paper.By introducing in-vasive weed optimization,the initial solution and the global best solution in each iteration process are se-lected.The problem of instability of nonlinear least-square method is solved.Given the determinate ele-ment number and array distribution,the phase of excitation is optimized to shape array pattern,whose sidelobe facing to ground is suppressed and back to ground descends by steps.Compared to unweighted pattern,the optimized pattern can reduce cluster level from the angle near main beam effectively.Simula-tion results prove the feasibility and efficiency of the method.%本文提出一种改进的非线性最小二乘算法(NLSM),通过引入入侵杂草算法(IWO)完成对初始解及迭代过程中的全局最优解的选取,解决了非线性最小二乘算法优化结果不稳定的问题.在阵列分布及单元个数一定的条件下,通过优化激励相位对相控阵天线方向图进行赋形,压低向地一侧峰值旁瓣电平,使背地一侧旁瓣电平递减变化.优化后的方向图可以有效降低中、近旁瓣杂波电平,证明了该算法的可行性和有效性.