卫星通信干扰信号识别技术研究现状及展望  

Overview of satellite communication interference signal recognition technology

作　　者：陈凤[1] 李聪[2] 朱立东[1] 吴琦[1] 乐秀权 戴志坚[3] CHEN Feng;LI Cong;ZHU Lidong;WU Qi;YUE Xiuquan;DAI Zhijian(National Key Laboratory of Wireless Communication,University of Electronic Science and Technology of China,Chengdu Sichuan 611731,China;Institute of Telecommunication and Navigation Satellites,China Academy of Space Technology,Beijing 100094,China;Shenzhen Institute for Advanced Study,University of Electronic Science and Technology of China,Shenzhen Guangdong 518110,China)

机构地区：[1]电子科技大学通信抗干扰全国重点实验室,四川成都611731 [2]中国空间技术研究院通信与导航卫星总体部,北京100094 [3]电子科技大学(深圳)高等研究院,广东深圳518110

出　　处：《太赫兹科学与电子信息学报》2024年第3期227-239,共13页Journal of Terahertz Science and Electronic Information Technology

基　　金：国家自然科学基金资助项目(62371098);基础加强资助项目(2020-JCJQ-ZD-119)。

摘　　要：随着通信技术的发展,卫星通信系统面临着日益严重的干扰问题以及干扰识别技术的挑战。针对这一现状,介绍了常见的卫星干扰信号样式及卫星干扰信号的发展趋势,分别从基于特征提取的干扰识别方法、传统机器学习方法以及深度学习方法3个方面介绍了卫星干扰信号分类识别技术的研究现状,分析了其各自的优势与不足。最后对未来卫星干扰信号分类识别技术进行了展望。Satellite communication,as an important means of communication,plays a key role in modern society.However,with the development of communication technology,satellite communication system is also facing the increasingly serious interference problem and the challenge of interference recognition technology.In view of this situation,this paper first introduces the common patterns of satellite interference signals,and summarizes the development trends of satellite interference signals.Secondly,the research status of satellite interference signal classification and recognition technology is introduced from three aspects:feature extraction based interference recognition method,traditional machine learning method and deep learning method,and their respective advantages and disadvantages are analyzed.Finally,the future classification and recognition technology of satellite interference signal is prospected.

关 键 词：卫星通信 干扰样式 干扰识别 深度学习 

分 类 号：TN927[电子电信—通信与信息系统]