基于神经网络改进时域滤波电力北斗抗干扰技术研究  

Research on Anti-jamming Technology of Power BeiDou Based on Neural Network Improved Time-domain Filtering

作　　者：董方云 吴赛 靳文鑫 滕玲 DONG Fangyun;WU Sai;JIN Wenxin;TENG Ling(Information&Telecommunication Institute,China Electric Power Research Institute,Beijing 100192,China)

机构地区：[1]中国电力科学研究院有限公司信息通信研究所,北京100192

出　　处：《自动化与仪表》2024年第12期18-22,27,共6页Automation & Instrumentation

基　　金：国网公司科技项目(5700-202218439A-2-0-ZN)。

摘　　要：北斗系统已经广泛应用于电力行业,在多种电力场景下起到关键作用。在变电站等强电磁干扰环境下,北斗信号难免会受到干扰。为了减小信号干扰,提高干扰环境下的定位授时精度,开展了北斗抗干扰相关技术研究。首先分析了变电站场景下的电磁干扰情况;其次提出一种利用神经网络改进北斗时域干扰抑制算法;最后在干扰环境下进行实地测试,验证了所提方法的效果。The BeiDou system has been extensively utilized in the power industry,serving as a key component in a variety of electrical scenarios.In environments with strong electromagnetic interference,such as substations,the BeiDou signals are bound to encounter disruptions.To minimize the impact of signal interference and improve the precision of positioning and timing within such environments,this study has conducted research on BeiDou anti-jamming techniques.Initially,the electromagnetic interference conditions in substation environments were analyzed.Subsequently,an improved BeiDou time-domain interference mitigation algorithm leveraging neural networks was proposed.Finally,on-site tests under jamming conditions were carried out to validate the effectiveness of the proposed approach.

关 键 词：北斗 电力 抗窄带干扰 神经网络 

分 类 号：TN967.1[电子电信—信号与信息处理] TP183[电子电信—信息与通信工程]