气象科学2026，Vol.46Issue(3)：298-306,9.DOI:10.12306/2025jms.0008
基于SE-UNet的天气雷达电磁干扰杂波识别技术
Indentification of weather radar electromagnetic interference clutter based on SE-UNet model
摘要
Abstract
The data quality issues caused by electromagnetic interference clutter account for more than 90％of all data quality problems in weather radar observations.Whenever these false data being incorporated into the base data,will introduce significant errors in precipitation estimation,backscatting analysis,and extrapolation of meteorological data.To better identify these abnormal echo returns and implement control measures to ensure the quality of weather radar observation data,this paper proposes an improved semantic segmentation approach based on deep learning,incorporating the SEBolock module into the U-Net model architecture to establish a new model,the SE-UNet model,for identifying electromagnetic interference clutter in weather radar.Based on the analysis and validation,the Mean Pixel Accuracy(MPA)and Mean Intersection-over-Union(MIoU)of the SE-UNet model both reached 99.9％,surpassing the performance metrics of SegNet,LinkNet,and U-Net models,which also having the lowest loss rate(Los).This indicates that the proposed model demonstrates high reliability in distinguishing electromagnetic interference clutter from precipitation returns.关键词
天气雷达/电磁干扰/SE-UNetKey words
weather radar/electromagnetic interference/SE-UNet分类
信息技术与安全科学引用本文复制引用
张二国,罗火钱,李雁,张林,张美新,苏静,燕若彤..基于SE-UNet的天气雷达电磁干扰杂波识别技术[J].气象科学,2026,46(3):298-306,9.基金项目
国家重点研发计划资助项目(2022YFC3090602) （2022YFC3090602）
中国气象局青年创新团队资助项目(CMA2024QN05) （CMA2024QN05）
中国气象局雷达气象重点开放实验室资助项目(2024LRM-B05) （2024LRM-B05）
福建省水利科技资助项目(MSK201911 （）
MSK202409) （）
