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卫星通信干扰信号识别技术研究现状及展望
引用本文:陈凤,李聪,朱立东,吴琦,乐秀权,戴志坚.卫星通信干扰信号识别技术研究现状及展望[J].太赫兹科学与电子信息学报,2024,22(3):227-239.
作者姓名:陈凤  李聪  朱立东  吴琦  乐秀权  戴志坚
作者单位: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
基金项目: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。

关 键 词:卫星通信  干扰样式  干扰识别  深度学习
收稿时间:2023/10/10 0:00:00
修稿时间:2024/1/8 0:00:00

Overview of satellite communication interference signal recognition technology
CHEN Feng,LI Cong,ZHU Lidong,WU Qi,YUE Xiuquan,DAI Zhijian.Overview of satellite communication interference signal recognition technology[J].Journal of Terahertz Science and Electronic Information Technology,2024,22(3):227-239.
Authors:CHEN Feng  LI Cong  ZHU Lidong  WU Qi  YUE Xiuquan  DAI Zhijian
Abstract: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.
Keywords:satellite communication  interference style  interference recognition  deep learning
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