改进粒子群算法及其在共形相控阵综合中的应用

在常规粒子群算法的基础上，通过引入新的速度更新算子、自适应边界控制算子和全局最优粒子扰动算子等操作，提出一种改进粒子群优化算法(IPSO); 并将该算法与简单二次插值算法相结合，克服了收敛速度慢，早熟及局部收敛等缺陷．进一步在对球面共形相控阵方向图综合时，引入了修正的波恩斯坦多项式以减少优化的变量，能够有效地加快算法的收敛速度．与常规粒子群算法和遗传算法的比较结果表明，该算法的局部搜索能力和全局搜索能力都有了很大程度的改善，从而证明了该方法在天线阵列综合中的有效性．

Improved particle swarm optimization and its application for conformal array pattern synthesis

By means of introducing such improved techniques as velocity updating, exceeding boundary control, perturbation of the global best particle, a new improved particle swarm optimization (IPSO) algorithm is proposed, which is further combined with the simplified quadratic interpolation method to overcome the drawbacks of the standard particle swarm optimization (PSO) algorithm, such as slow convergence, prematurity and easily trapping in local optimum. A modified Bernstein polynomial is used to reduce the number of variables when calculating the pattern function of the spherical conformal array. Simulation results show that the pinpointing search ability and the global search ability of the proposed algorithm are significantly improved compared with the standard particle swarm optimization and genetic algorithm (GA), thus proving the effectiveness of the proposed algorithm for antenna synthesis.