天线匹配网络拓扑优化:理论建模与数值实验  

Topology optimization of antenna matching networks:Theoretical modeling and numerical experiments

作　　者：周子恒 苏梓暄 周彦峰 张哲晨 许志猛[1] 陈志璋 ZHOU Ziheng;SU Zixuan;ZHOU Yanfeng;ZHANG Zhechen;XU Zhimeng;CHEN Zhizhang(College of Physics and Information Engineering,Fuzhou University,Fuzhou 350108,China;Department of Electrical and Computer Engineering,Dalhousie University,Halifax,NS B3H 4R2,Canada)

机构地区：[1]福州大学物理与信息工程学院,福建福州350108 [2]Department of Electrical and Computer Engineering,Dalhousie University,Halifax,NS B3H 4R2,Canada

出　　处：《实验技术与管理》2024年第11期1-7,共7页Experimental Technology and Management

基　　金：国家自然科学基金项目(62301162,12304056);福建省自然科学基金项目(2023J01058);福州大学科研启动项目(XRC-23007,XRC-24016,XRC-23012);福州大学研究生教育教学改革项目(048363,FYAL2023014)。

摘　　要：拓扑优化方法因其高自由度特点在器件智能设计领域发挥重要作用,在微波工程课程中引入器件拓扑优化实验可提升课程前沿性。该实验通过天线匹配网络拓扑优化提高天线的辐射性能:首先采用阻抗矩阵方法对天线匹配网络的响应进行理论建模,随后利用遗传算法对网络进行拓扑优化,实现天线工作频带的智能按需设计。结果表明,经过拓扑优化的微波天线可在指定的频带内实现良好的阻抗匹配,达到95%以上的最大天线效率。该实验展示了基于阻抗矩阵理论的微波网络拓扑优化方法,为微波与天线相关课程提供了一项具备综合性、前沿性的课题训练项目。concepts in the microwave theory and network theory more easy to comprehend,this not only bridges classroom knowledge with advanced industrial design techniques but also cultivates students’analytical,modeling,and engineering skills.[Methods]Using concrete examples of antenna matching network optimization,the experiment reported in this study explores the method and implementation techniques of topology optimization.The investigated network topology optimization experiment involves two interconnected phases:theoretical modeling and numerical optimization.Initially,this study uses the impedance matrix approach for the accurate and fast modeling of a grid-like antenna matching network.Once the connection relationship in the matching network is determined,a closed-form expression of the network scattering parameters can be obtained explicitly,eliminating the need for computationally expensive full-wave simulations and thus accelerating the forward problem solving during each iteration of topology optimization.Subsequently,a genetic algorithm,which is a type of powerful stochastic optimization algorithm,is leveraged to optimize the connection relationship in the grid-like network,achieving an intelligent on-demand design of the antenna operating frequency band.The genetic algorithm can handle the ill-posed optimization problem using mechanisms such as selection,crossover,and mutation to yield solutions that approximate the optimal solution of the search process.[Results]This study demonstrates the resultant structures and performances of topology-optimized narrow-bandwidth monopole antennas operating at center frequencies of 1.00,1.20,and 1.40 GHz,as well as a wideband antenna operating in the range of 1.099–1.395 GHz.The narrow-bandwidth design is achieved by introducing a single resonance of the matching-network-loaded antenna that closely matches the prescribed center frequency,while the wideband design emerges from creating two resonances with an appropriate frequency separation.Two important figures of merit

关 键 词：拓扑优化 智能设计 阻抗矩阵 天线匹配网络 

分 类 号：G642[文化科学—高等教育学] TN820[文化科学—教育学]