低峰值旁瓣电平稀布阵综合算法研究

摘要

针对稀布阵具有较高峰值旁瓣电平(PSLL)的问题,从阵元对称与否、阵元数奇偶及天线阵列有无栅瓣这三个角度分析、对比了粒子群算法和三种遗传算法进行稀布阵综合的优缺点,并进一步分析了阵元数目、阵列孔径和最小阵元间距对稀布阵PSLL的影响.为进一步降低PSLL,提出在适应度函数中加改进海明窗的方式进行稀布阵阵元位置优化,通过仿真验证了方法的正确性和适用性.%To resolve the problem of high peak side-lobe level(PSLL) of sparse array,this paper analyzes and compares the feasibilities of particle swarm optimization and three kinds of genetic algorithms which are adopted to optimize the position of sparse array elements through determination of the symmetry of sparse array,the parity of element number of sparse arrays,and the existence of grating lobe.Additionally,the influences of the number of sparse array elements,the aperture,and the minimum distance on PSLL are analyzed.The article proposes an idea to decrease PSLL further by introducing the improved Hamming window into the fitness function.