改进哈里斯鹰算法用于阵列天线方向图赋形

Improved Harris hawks algorithm for pattern shaping of linear antennaarrays

由于目前群智能优化算法在解决直线阵列天线方向图的旁瓣电平抑制和零陷控制问题时容易陷入局部最优以及收敛速度较慢的问题,提出了一种改进哈里斯鹰优化算法。该算法首先引入单鹰探索策略来扩大算法的全局搜索范围,然后引入自适应控制理论,用以提高算法的搜索精度并加快算法的收敛。仿真结果表明,与粒子群算法、布谷鸟搜索算法、蚁群优化算法以及标准哈里斯鹰优化算法相比,所提算法在压低直线形阵列天线方向图的旁瓣电平和控制零陷方面更具优越性。

In order to better solve the problem about side lobe level suppression and nulls control of linear antenna arrays,an improved Harris hawks algorithm(IHHA)is proposed.The algorithm first uses a single eagle search strategy to expand the global search scope of the algorithm,and then introduces adaptive control theory to improve the search accuracy of the algorithm and ac-celerate the convergence of the algorithm.The simulation results show that compared with particle swarm optimization,cuckoo search algorithm,ant colony optimization algorithm and standard Harris hawks optimization algorithm,the proposed algorithm has more advantages in reducing the side lobe level and controlling nulls of the linear antenna arrays.