粒子群优化算法在无人分布式阵面的应用

Application of particle swarm optimization algorithm in unmanned distributed ar‐ray

机载雷达受限于载机平台,无法获得更大口径的阵面,而在无人机平台,可将雷达阵面化整为零,在有限阵元数条件下,采用稀布阵列可获得更大口径的阵面。然而稀布阵列造成方向图栅瓣和副瓣的抬高,需对稀布阵列进行优化,消除栅瓣、降低副瓣后方能使用。稀布阵列方向图优化是一个离散优化问题,将粒子群优化算法应用于无人分布式雷达的稀布阵列上,其算法原理简单,运行速度快,可调参数少,以较少的阵元数获得无栅瓣和低副瓣的方向图,从而提升无人分布式阵面的性能。

Airborne radar is limited by the carrier platform and cannot obtain a larger aperture array,while on unmanned aerial vehicle platforms,the radar array can be reduced to zero.Under the condition of finite array elements,a sparse array can be used to obtain a larger aperture array.However,sparse array can cause the elevation of directional grid lobes and side lobes,and it needs to be optimized to eliminate grid lobes and reduce side lobes before it can be used.The optimization of sparse array pattern is a discrete optimization problem.In this paper,the particle swarm optimization algorithm is applied to the sparse array of unmanned distributed radar.The algorithm principle is simple,the running speed is fast,the adjustable parameters are few,and the directional pattern without grid lobes and low sidelobes is obtained with fewer array elements,thereby improving the performance of unmanned distributed array.