基于二分粒子群优化的阵列天线方向图综合

Array Antennas Beam Pattern Synthesis Based on Dichotomic Particle Swarm Optimization

在阵列方向图综合中,粒子群优化技术通过简单的算法就可以达到很好的综合效果。然而基本的粒子群算法存在易于陷入局域最优值、迭代次数大的缺点,针对这些缺点,提出了一种新的算法——二分粒子群优化算法。该算法利用基本粒子群算法中的随机因素将其下一代的粒子分裂为2个粒子,在这2个粒子中选优处理。仿真结果表明,改进算法改善了基本粒子群算法容易收敛到局域最优值和迭代次数大的缺点,在阵列方向图的综合中取得了良好的效果。

At the beam pattern synthesis of array antennas, particle swarm optimization （PSO） can obtain a good synthesis effect by using simple arithmetic. But the basic PS0 has some disadvantages, such as tending to partial best value, having an iterative time. Aiming at these disadvantages, a new arithmetic： dichotomic particle swarm optimization（DPS0） is proposed. The method breaks up the next particle into two by using stochastic factors of the basic PSO and choosing the better particle. The simulation results show that the improved method eliminates the disadvantages of the basic PSO and achieves a good effect in the beam pattern synthesis of array antennas.