针对双频非周期阵列波束综合问题,提出了一种将遗传算法与差分进化算法结合的优化算法(GA-DE混合优化算法)。该优化算法在每轮迭代时先利用差分进化算法生成与遗传算法相同规模的种群,将该种群与原种群混合后保留适应度较好的个体,然后再由遗传算法进行迭代优化;同时对遗传算法的选择、交叉、变异算子做出改进,提升了算法的全局搜索能力和收敛速度。通过与其他算法对比验证,混合优化算法可以优化得到更优的副瓣电平和增益,仿真结果表明该算法具有良好的性能。利用混合优化算法在保证阵列增益的条件下,以降低峰值副瓣电平为目标优化Ku/ Ka双频混排标准化子阵和Ku/Ka双频混排整阵。优化后Ku和Ka整阵在扫描范围内最大峰值副瓣电平分别为-13. 10 dB 和-13. 13 dB,最小增益分别为44. 81 dB和44.58 dB,达到了指标要求,优化结果说明混合优化算法可以有效抑制非周期阵列栅瓣的出现和降低阵列的峰值副瓣电平。

To solve the problem of dual-frequency aperiodic array pattern synthesis, an optimization algorithm that combines genetic algorithm and differential evolution algorithm is proposed(GA-DE hybrid optimization algorithm). The optimization algorithm firstly uses the differential evolution algorithm to generate a population of the same size as the genetic algorithm in each iteration, mixes the population with the original population and retains individuals with better fitness, and then uses the genetic algorithm to iteratively optimize. At the same time, the selection, crossover and mutation operators of the genetic algorithm are improved, which improves the global search ability and convergence speed. Compared with other algorithms, the hybrid algorithm can be optimized to obtain better sidelobe level and gain. This simulation results show that the algorithm has good performance. Under the condition of ensuring the array gain, the hybrid optimization algorithm is used to optimize the Ku/ Ka dual-frequency mixed normalized subarray and Ku/ Ka dualfrequency mixed whole array with the goal of reducing the peak sidelobe level. After optimization, the maximum peak sidelobe levels of the Ku and Ka arrays in the scanning range are -13. 10 dB and -13. 13 dB respectively, and the minimum gains are 44. 81 dB and 44. 58 dB respectively, which meet the index requirements. The optimization results shows that the hybrid algorithm can effectively suppress the appearance of the aperiodic array grating lobes and reduce the peak sidelobe level of the array.

TN957. 52

河北省人才工程资助项目(A202101006)