天线辅助设计IGA方法

A novel immune genetic algorithm for antenna design

摘要:

为了高效设计高性能的天线,将免疫遗传算法引入天线辅助设计领域.在传统遗传算法的基础上增加抗原识别、记忆功能和浓度调节,同时引入一种新型的混合编码技术简化天线结构描述及交叉、变异等遗传操作,实现天线结构的快速优化设计.仿真结果表明,相比传统遗传算法,在天线结构设计中应用免疫遗传算法,迭代次数明显减少,收敛速度提高50%～60%,算法执行效率显著提高,在频率为8.47GHz时设计所得天线的最大平均增益和最小平均增益分别提高119.91%和258.89%,性能优异.免疫遗传算法克服了遗传算法由于交叉搜索而在局部搜索解空间时效率较差的缺点,有效地避免了未成熟收敛的问题,收敛稳定且速度明显加快,体现了免疫遗传算法在天线辅助设计中的优异性和高效性.

Abstract:

The immune genetic algorithm (IGA) was introduced into the fast optimization of antenna design.By employing antigen recognition,concentration regulation as well as memory mechanism,and adopting a new hybrid encoding to simplify the description of antenna structure and the operations of crossover and mutation;the fast optimization of antenna structure was realized.;The simulation of ST5 satellite antenna was carried out to verify the proposed method.Results show that the iteration times are reduced evidently in the antenna design,the convergence rate is sped up about 50%-60%.The maximum and minimum average gains for the designed antenna at 8.47 GHz are increased by 119.91% and 258.89%,respectively.Compared with traditional genetic algorithms,IGA overcomes their shortcomings in local search and avoids the problem of immature convergence,which proves the effectiveness of IGA in the antenna design.