基于改进的粒子群算法的二维阵列天线方向图综合技术
doi: 10.3724/SP.J.1146.2005.01375
Pattern Synthesis of 2-D Arrays Based on a Modified Particle Swarm Optimization Algorithm
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摘要: 该文运用一种改进的粒子群优化算法对不等幅激励的矩形平面阵列天线的最大旁瓣电平进行了优化，采用对全局最优粒子微扰和跳变的惯性权重策略，并使用粒子群算法本身对参数组合进行了优化选择。新算法大大改善了优化速度和收敛精度。对二维阵列天线旁瓣电平优化和稀疏阵列方向图综合的良好结果也证明了该方法的有效性。Abstract: A modified Particle Swarm Optimization (PSO) algorithm is proposed and used to optimize the sidelobe level of plane arrays, in which special techniques as global best perturbation and jumped inertia weight strategy are adopted. The PSO algorithm is also used to select a better combination of optimal parameters for itself. So that the convergent speed and accuracy of the algorithm are improved. The simulation results of sidelobe reduction of 2-D arrays and pattern synthesis of a sparse array show that it is effective.
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