平面阵子阵级自适应波束形成方法研究

利用遗传算法(GA)将大型阵列划分为非均匀邻接子阵,以主旁瓣比作为适应度函数,并对遗传操作增加约束条件,得到具有栅瓣抑制能力的子阵结构。为进一步抑制平面阵俯仰和方位上的高旁瓣,对平面阵进行两级子阵划分,使平面阵方向图在俯仰和方位上均具有良好的主旁瓣电平比;为消除非均匀子阵结构各子阵通道噪声功率不同对子阵级自适应波束形成算法的影响,通过对阵列协方差矩阵进行奇异值分解、重构特征子空间,提出了基于特征空间重构的子阵级自适应波束形成方法。仿真结果表明了该方法的可行性与有效性。

Research on Adaptive Beamforming Method at Subarray Level for Planar Array

An effective subarray partition method based on genetic algorithm（GA） is proposed to divide a large array antenna into contiguous subarrays of unequal sizes. In the genetic algorithm, the main-to side lobe ratio（MSR） of pattern is taken as the fitness function. A subarray configuration with few obvious grating lobes is obtained by adding constraint condition in the genetic evolvement. A two-stage suharray partition method based on genetic algorithm（GA） is proposed to divide a planar array antenna into contiguous subarrays with ununiform structure. Using the two-stage subarray configuration, its pattern has high main-tosidelobe ratio（MSR） in both the azimuth and elevation orientations. For the purpose of avoiding the influence of unequal noise power out of each subarray, an effectively adaptive beamforming algorithm based on singular value decomposition and eigenspace reconstruction is obtained. The simulation results are given to demonstrate the effectiveness and accuracy of this method.