基于改进遗传算法的非均匀稀布阵列优化

提出了一种对非均匀稀布阵列阵元间距进行优化的改进的遗传算法。该算法在编码时，将阵元间距依据尺寸步长划分为不同的节点，通过对节点的二进制编码，灵活实现带约束阵元间距的遗传编码。在遗传操作过程中，依据不同的进化阶段自适应设定算子系数，有效地提高了遗传算法的收敛性。文中采用同时考虑副瓣电平和渡束宽度的双适应度函数，使优化得到的天线阵列方向图比采用单适应度函数有较好的综合性能。最后通过大量仿真结果验证了这一算法的有效性。

Optimal Design of Nonuniform Sparse Arrays Based on Modified Genetic Algorithm

A modified genetic algorithm is presented to optimize the element spacing of the nonuniform sparse array in this paper. In the algorithm, the element spacing with restriction is divided into different nodes according to the step, after that the nodes are encoded into hinary codes. The faster convergence can be obtained by adaptively modifying the operator coefficients in different phases. Compared with fitness function, using bi-fitness function considering both sidelobe level and mainlobe width, the better synthetical performance of the array pattern can be obtained. The simulated results demonstrate the feasibility of the algorithm.