通信辐射源个体识别中的特征提取方法综述  

Overview of Radio Frequency Fingerprint Extraction in Communication Specific Emitter Identification

作　　者：韦建宇 俞璐 WEI Jianyu;YU Lu(Army Engineering University of PLA,Nanjing Jiangsu 210007,China)

机构地区：[1]中国人民解放军陆军工程大学,江苏南京210007

出　　处：《通信技术》2022年第6期681-687,共7页Communications Technology

摘　　要：辐射源个体识别技术,又称辐射源指纹识别或特定辐射源识别(Specific Emitter Identification,SEI),是指通过对接收的电磁波信号的特征进行提取测量,根据已有的先验知识从而识别出发射该电磁波信号的辐射源个体的技术。相比于其他辐射源,通信辐射源的特征更加细微,提取更加困难。通过系统梳理近年来通信辐射源特征提取方法的研究现状,从暂态特征、稳态特征以及深度学习特征提取的角度分析了各种方法的优缺点,还分析了个体识别技术重点和难点所在,希望对辐射源个体识别的研究和应用有所帮助。The individual radiation source identification technology,also known as radiation source fingerprint identification or SEI(Specific Emitter Identification),refers to the technology which extracts and measures the features of the received electromagnetic signal,and then identifying the individual radiation source that emits the electromagnetic wave signal according to the existing prior knowledge.Compared with other radiation sources,the features of communication radiation sources are more subtle and more difficult to extract.This paper systematically sorts out the current research status of feature extraction methods for communication radiation sources in recent years,analyzes the advantages and disadvantages of various methods from the perspective of transient features,steady-state features and deep learning feature extraction,and analyzes the key points and difficulties of individual identification technology,hoping to help the research and application of individual identification of radiation sources.

关 键 词：辐射源识别 射频指纹特征提取 深度学习 信号处理 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TN975[自动化与计算机技术—控制科学与工程]