基于实数编码遗传算法的稀布阵列综合

针对有孔径和阵元总数约束的线性阵列，提出了一种基于实数编码遗传算法的稀布阵列综合方法。算法中每条染色体基因主要由阵元间距和激励幅度共同组成，采用双变量组合优化的方式为阵列性能优化提供了更多的自由度。采用十进制实数量化编码的方式，省去了二进制编码过程中的解码运算，使算法程序更为简洁，效率更高。以降低阵列方向图的峰值旁瓣电平为目标函数，运用提出的改进遗传算法针对几种不同的线性阵列进行优化仿真，在同等约束条件下将该算法与其他改进遗传算法进行了优化对比，结果表明该算法表现更为出色。

Sparse array synthesis based on real coded genetic algorithm

For linear arrays with constraints of aperture and a total number of array elements,a sparse array synthesis method of genetic algorithm(GA) based on real coding is proposed.In the algorithm,each chromosome gene is mainly composed of element spacing and excitation amplitude,and the bivariate combinatorial optimisation provides more freedom for array performance optimisation.The decimal real quantisation coding method omits the decoding operation in the binary coding process,making the algorithm program more concise and more efficient.In order to reduce the peak sidelobe level of the array pattern as the objective function,the improved GA is used to optimize and simulate several different linear arrays.Then this algorithm is optimized and compared with other improved GAs under the same constraints.The results show that the performance of the proposed algorithm is better.