利用GEK代理模型的天线快速多目标优化设计

传统方法进行天线优化设计主要利用经典优化算法调用电磁仿真软件，在求解复杂天线的多目标优化问题时效率不理想．针对该问题，在多梯度下降算法中引入遗传算子，提出了一种高效的全局多目标优化算法--混合遗传算子多梯度下降算法．该算法调用梯度增强型克里金模型进行天线优化．梯度增强型克里金模型建模所需的样本规模小、时间短，并且避免了电磁仿真软件的反复计算．利用该算法优化加载各向异性Ⅰ型周期结构覆层的警用超短波宽带单极子天线和某型直升机机载专用通信系统天线及其抗干扰阵列，在达到相同优化效果时，所需的模型仿真次数为利用改进的非支配排序遗传算法调用电磁仿真软件进行优化的10.30％和18.96％，验证了该优化算法的高效性．

Expedited antenna multi-objective optimization method based on gradient-enhanced kriging surrogate model

Based on classical optimization algorithms and electromagnetic simulations, traditional antenna optimization method is inefficient, especially when it is used to solve the complex antenna multi-objective optimization problem. With the introduction of the genetic operator, the paper proposes an efficient global optimization algorithm named the Multi-Gradient Descent Algorithm Hybrid with the Genetic Operator to alleviate the problem above. For the merits of quick establishment and reduced samples scale, the Gradient-Enhanced Kriging(GEK) model is invoked by the proposed algorithm as the surrogate of antenna electromagnetic analysis. A Novel broadband UHF monopole antenna enabled by anisotropic Ⅰ-shaped periodic structure cladding and a dual-band UHF antenna together with its anti-jamming array antenna reserved for the private airborne communication system are designed with the proposed optimization method. The necessary electromagnetic simulation time of the proposed method is 10.30％ and that of the traditional optimization method is 18.96％, which verifies the merit of high efficiency.