无线电工程2026，Vol.56Issue(5)：761-769,9.DOI:10.3969/j.issn.1003-3106.2026.05.001
特征模理论与机器学习协同辅助的宽带小型化天线设计
Design of Broadband Miniaturized Antennas Synergistically Assisted by Characteristic Mode Theory and Machine Learning
摘要
Abstract
A broadband miniaturized Microstrip Patch Antenna(MPA)is proposed,which extends the current path and enhances the reactive loading effect by loading a slot structure on the antenna's radiating patch,thereby lowering its resonant frequency to achieve miniaturization.The Characteristic Mode(CM)theory is used to analyze the working mechanism of the radiating unit and guide the selection of the feed position to ensure the desired mode resonates.An air layer is introduced between the two substrates to broaden the antenna's bandwidth.Additionally,machine learning is introduced to optimize the parameter performance,overcoming the drawbacks of traditional tools,such as the large amount of parameter sweep data and high time consumption,ultimately achieving an operating frequency of 6.15～11.45 GHz(relative bandwidth of 60%)and a size of 0.43λ0×0.43λ0×0.12λ0.Compared to traditional microstrip antenna size of 0.6λ0×0.6λ0×0.17λ0,the overall size is reduced by 63%.关键词
微带天线/特征模/宽带小型化/机器学习Key words
microstrip antenna/CM/broadband miniaturization/machine learning分类
信息技术与安全科学引用本文复制引用
温乐乐,尤智源,高瑞,赵晔,何智慧..特征模理论与机器学习协同辅助的宽带小型化天线设计[J].无线电工程,2026,56(5):761-769,9.基金项目
延安大学研究生实践创新计划(YSJ2026022) （YSJ2026022）
延安大学科研计划(GXYQ001) Graduate Practice Innovation Program of Yan'an Univer-sity(YSJ2026022) （GXYQ001）
Scientific Research Program of Yan'an University(GXYQ001) （GXYQ001）
