一种新的稀疏直线阵列波束形成算法

A new sparse linear array beam forming algorithm

为了提高稀布阵列天线的综合性能,稀布阵列天线不仅要有窄波束和高增益,还需要有稳健的波束形成算法,以增强其目标识别的能力和抑制干扰的能力。本文以稀疏直线阵列为基本模型,在遗传算法和特征投影及协方差矩阵重构(EP-CMR)算法的基础上,提出了一种新的稀疏直线阵列波束形成算法。该算法将方向图最大旁瓣电平作为适应度函数,通过不断优化阵元的位置,使得基于遗传算法及EP-CMR算法的稀疏直线阵列方向图的最大旁瓣电平最小。实验结果显示,本文算法不但能有效抑制主瓣干扰和旁瓣干扰,同时还可以减少天线阵元、降低成本,抑制阵列天线方向图的旁瓣电平。

In order to improve the comprehensive performance of the sparse array antenna,the sparse array antenna should not only have narrow beam and high gain,but also need to have robust beam forming algorithm to enhance its target recognition ability and restrain interference. Taking sparse linear array as the basic model,this paper proposes a sparse linear array beam forming algorithm based on genetic algorithm and eigen-projection processing and covariance matrix reconstruction algorithm based on genetic algorithm and eigen-projection processing and covariance matrix reconstruction algorithm. This algorithm takes the maximum sidelobe level of the direction map as the fitness function,and makes the maximum sidelobe level of the sparse linear array direction map based on genetic algorithm and eigen-projection processing and covariance matrix reconstruction algorithm to be minimum by continuously optimizing the position of the array element. The simulation results show that the proposed algorithm can not only effectively suppress the main lobe interference and side lobe interference,but also can reduce the number of antenna arrays and cost,and at the same time can suppress the sidelobe level of the antenna pattern.