针对阵列天线计算中采用传统遗传算法收敛速度慢,且种群多样性有限的弊端,提出了一种对直线阵及矩形平面阵进行稀布处理的混合算法。主程序使用遗传算法作为全局搜索器进行全局寻优,使用和声搜索算法作为局部搜索器,通过不断生成新个体以替换种群中的最差个体,进而提高个体遗传特性,避免算法过早收敛于局部最优解。构建了遗传算法自适应函数,采用混合交叉策略提高了种群多样性。仿真结果表明,提出的混合算法提高了稀布阵天线算法的收敛速度,降低了阵列天线旁瓣电平,具有一定的可行性。

Aiming at the disadvantages of the slow convergence speed of the traditional genetic algorithm and the limited population diversity in the calculation of the array antenna, a hybrid algorithm for sparsely processing the linear array and the rectangular planararray is proposed. The main program uses genetic algorithm as the global searcher for global optimization, and the harmony search algorithm as the local searcher. By continuously generating new individuals to replace the worst individual in the population, the genetic characteristics of individuals are improved and avoided premature convergence of the algorithm to the local optimal solution. A genetic algorithm adaptive function is constructed, and a hybrid crossover strategy is adopted to improve the diversity of the population. The simulation results show that the proposed hybrid algorithm improves the convergence speed of the sparse array antenna algorithm and reduces the sidelobe level of the array antenna, which is feasible.

TN926.4