文中采用自适应量子粒子群算法(AQPSO),对基站阵列天线进行多目标波束形成,在期望信号方向形成主波束,在干扰信号方向形成零陷,同时压制副瓣电平。该算法引入自适应加速因子和动态量子旋转门,提高算法收敛速度以及全局寻优能力,加入阵元数据,提高赋形效果与实际情况的吻合度。比较AQPSO算法、粒子群算法(PSO)和遗传算法(GA)的方向图综合性能,证明了AQPSO算法具有快速收敛、全局寻优的特性。

The adaptive quantum particle swarm algorithm (AQPSO) is adopted to perform multi-objective beam forming and control the sidelobe level for base station array antennas. The main beam is formed in the desired signal direction. The null pattern is formed in the direction of interference signal. The real coding is adopted to reduce the complexity of algorithm. The adaptive optimization factor is introduced to improve the convergence speed of the algorithm. The dynamic quantum rotation gate is introduced to enhance the global optimization ability of the algorithm. The data of array element is combined to improve the agreement of synthesized pattern and actual pattern. Comparing the synthesis performance of AQPSO, particle swarm optimization (PSO) and genetic algorithm (GAPSO), it is concluded that AQPSO has the characteristics of fast convergence and global searching.