遗传算法在相控阵子阵量化随机馈相中的应用

在大型相控阵中 ,为了减少昂贵的数字移相器 ,一般采用子阵技术。但这带来新的问题 ,子阵相位量化时 ,采用前一个单元的相位还是采用后一个单元的相位 ,是舍去还是进入 ,这些问题给子阵相位量化的分析增加了复杂性。文中在子阵量化随机馈相的基础上 ,采用遗传算法对子阵量化中各种随机馈相的方案进行优化 ,并给出应用实例 ,取得了令人满意的优化结果

Application of Genetic Algorithm in Randomizing Phase Feeding of Phased Arrays Sub-array Quantization

In large scale phased arrays,the sub array technique is applied to reduce the number of expensive digital shifters. But it also brings new problems,when sub array phase quantization, which phase should be chosen,the former or the later element?whether give up or carry?all these make the analysis of sub array phase quantization more complicated. At the basis of sub array quantization randomizing phase feeding, this paper uses genetic algorithm to optimize the randomizing phase feeding. It gives a optimization example, and get a good result.