基于遗传算法的不等间距阵优化方法*

阵元数一定情况下，针对不等间距拖线阵高频信号处理存在的空间增益和无栅瓣兼容问题，提出一种基于遗传算法的不等间距拖线阵阵型优化方法。该方法以频带交互下最大旁瓣级最小作为约束因子，通过模拟生物自然进化过程搜索全局最优解，得到优化后的阵元位置。优化后阵型在保证低频信号处理空间增益不变情况下，实现对高频信号高空间增益、无栅瓣处理。计算机仿真结果表明：相比未优化阵型，在高频信号处理方面，优化后阵型在无栅瓣情况下，空间增益提升值近似理论值提升值；在低频信号处理方面，优化后阵型具有相同的空间增益。为实际不等间距拖线阵阵型优化和应用提供了一种思路。

Unequally spaced array optimization based on genetic algorithm

In the case of a certain number of array elements, for the compatibility problem of spatial gain and non-grating lobe existing in high-frequency signal processing of unequally spaced towed linear array, an optimization method of unequally spaced towed linear array based on genetic algorithm was proposed. The constraint factor was taken via minimum maximum side-lobe level under the frequency band interaction, and the global optimal solution by simulating the natural evolution process of biology was searched, then the optimized position of the array element was obtained. Under the condition that the gain of the low-frequency signal processing array remains unchanged, the optimized array could achieve high-gain, no grating lobe detection for high-frequency signals. The results of verification analysis show that, compared with the original array, in high-frequency signal processing, the optimized array has no grating lobes, and the spatial gain is similar to the theoretical value, in the low-frequency signal processing, the optimized array has the same array gain. That provides an idea for unequally spaced towed linear arrays optimization and application.