大型阵列天线子阵划分及栅瓣抑制方法

Subarray Partition Method and Grating Lobe Suppression for Large Array Antenna

  • 摘要: 利用遗传算法(genetic algorithm, 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。提出了基于子阵级的波束扫描方法,在每个扫描分区内无需改变阵元权值,仅通过子阵级数字波束形成即可完成阵列的波束扫描,并分析了不同扫描角对阵列方向图的影响。为了抑制大扫描角带来的高旁瓣,运用自适应原理使子阵级方向图在高旁瓣位置形成凹陷。分析与仿真结果表明,该方法能够进一步提高阵列方向图的主旁瓣比,增加扫描分区的范围。

     

    Abstract: An effective subarray partition method based on genetic algorithm (GA) is proposed to divide a large antenna array into contiguous subarrays with ununiform structure. In the genetic algorithm,the main-to-sidelobe ratio (MSR) of pattern is taken as fitness function. A subarray configuration with few obvious grating lobes is obtained by adding constraint condition in the genetic evolvement. A new method of beam scanning at subarray level is presented for the purpose of reducing the grating lobe by dividing the scanning region. In each scanning regional division, the beam scanning can be realized by beamforming at subarray level without adjustment of elements’ weights. In addition, the affection of different scanning angles on the array pattern is analyzed. To suppress the high level of sidelobes, subarray pattern has formed nulls in the directions of high sidelobes referring to adaptive array theory. Theoretical analyses and simulation results show that the main-to-sidelobe ratio of array pattern can be further improved, and also the range of scanning regional division is extended.

     

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