电子科技2025，Vol.38Issue(7)：34-39,6.DOI:10.16180/j.cnki.issn1007-7820.2025.07.005
神经网络辅助双频U型槽贴片天线优化
Dual-Band U-Slot Patch Antenna Optimization Using Neural Network Model
摘要
Abstract
In order to improve the efficiency of antenna design,a double-frequency U-slot patch antenna based on PSO-BPNN(Particle Swarm Optimization-Back Propagation Neural Network)model is designed using machine learning to assist antenna optimization design.The operating frequency covers IEEE802.11y(3.65 GHz)and IEEE802.11a(5.20 GHz),and is compared with the antenna designed based on PSO algorithm.According to the simulation model,the antenna is fabricated and tested.The results show that at the resonant frequency of 5.20 GHz,the antenna return loss designed by PSO-BPNN model and PSO model algorithm is close.At the resonant frequency of 3.65 GHz,the return loss of the antenna designed based on the PSO-BPNN model is-22.65 dB and the imped-ance bandwidth is 0.205 GHz,which is 47.85%and 11.41%higher than that designed by the PSO algorithm,re-spectively.Test results reveal that the radiation characteristics of the antenna designed based on the PSO-BPNN model algorithm are in good agreement with the measured results.关键词
BP神经网络/粒子群算法/天线优化设计/双频/贴片天线/U型槽/电磁仿真/回波损耗Key words
BP neural network/particle swarm algorithm/antenna optimization design/dual frequency/patch an-tenna/U-slot/electromagnetic simulation/return loss分类
信息技术与安全科学引用本文复制引用
张斌,丁海兵,王晶,薛谦忠..神经网络辅助双频U型槽贴片天线优化[J].电子科技,2025,38(7):34-39,6.基金项目
国家自然科学基金(12075247)National Natural Science Foundation of China(12075247) （12075247）
