一种改进粒子群算法的立体阵列优化方法

利用传统粒子群算法对立体阵列所有臂的阵元分布形式同时进行优化时,不仅耗时,而且易于收敛到局部解。为了解决这个问题,提出了一种改进粒子群算法(Improved Particle Swarm Optimization,IPSO)。改进算法采用并行计算思想,同时初始化多个粒子群,每个粒子通过优化一个臂(优化臂)的阵元参数达到"降维"的目的,使用线性递减惯性权重,对多个粒子群同时进行预优化,获得中间解。利用中间解构建一个"升维"的新粒子,使用最小惯性权重对新粒子继续优化,满足停止条件后输出。通过对5臂星形立体阵列进行优化设计,发现改进算法不仅耗时短,而且能够得到更优的结果,最后通过6个仿真实验讨论了所设计的阵列的指向特性。

An improved particle swarm optimization algorithm for 3D array optimization

Since using the traditional particle swarm optimization (TPSO) algorithm simultaneously to optimize the form of all 3D array elements takes a long time and is easy to converge to a local result.An improved particle swarm optimization (IPSO) algorithm based on the parallel computing idea is presented in this paper.The multiple particle swarms are initialized simultaneously,and the dimension reduction of each particle is achieved by means of optimizing the parameters of an array arm (optimized arm) only.Subsequently,by using the linearly decreasing inertial weight to pre-optimize the multiple particle swarms at the same time,the intermediate solution is obtained to form the new particle with regained dimension.The new particle swarm optimization process continues with the least inertia weight to output the solution until the stop condition is satisfied.A 5-arm star-shaped 3D array is optimized and designed in this paper,it is found that the computing time is reduced and it can obtain a better result for the IPSO algorithm.At the end of this paper,the six simulation tests are used to discuss the characteristics of the arrays designed in this paper.