基于粒子群优化的圆阵列波束形成方法

围绕均匀圆阵列(uniform circular array, UCA)在波束形成中存在的波束主瓣宽、旁瓣电平高的问题,提出了一种基于粒子群优化(particle swarm optimization, PSO)算法的圆阵列波束形成方法。通过对UCA的输出信号进行模式空间变换,将UCA数据转换为虚拟均匀线阵数据形式。利用PSO算法充分挖掘均匀线阵各阵元间数据信息,进行阵元拓展,从而实现阵列阵元数及孔径尺度的增加,实现降低阵列波束主瓣宽度及旁瓣电平的目的。实验结果表明,在适当增加计算复杂度的前提下,利用PSO算法对阵列进行阵元拓展可以显著地提高波束形成质量,且适用于自适应波束形成。

Circular array beamforming method based on particle swarm optimization

To solve the problem of wide main lobe and high side lobe level in beamforming of the uniform circular array (UCA), a circular array beamforming method based on particle swarm optimization (PSO) algorithm is proposed. Through the mode space transformation of the output signal of the UCA, the receive data on the UCA is converted into a virtual uniform linear array data form. The PSO algorithm is used to fully exploit the data information among the elements of the uniform linear array and expand the array elements, so as to increase the number of the elements and aperture scale of the array and reduce the main lobe width and side lobe level of the array beam. The experimental results show that under the premise of properly increasing the computational complexity, the quality of beamforming can be significantly improved by using the PSO algorithm to expand the array elements, and it is suitable for adaptive beamforming.