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针对细微特征进行K-means聚类的电台分选识别技术
引用本文:杨亮亮.针对细微特征进行K-means聚类的电台分选识别技术[J].电讯技术,2022,62(8).
作者姓名:杨亮亮
作者单位:中国西南电子技术研究所,成都 610036
摘    要:现代战场中的无线通信设备日益增多,精准获取个体信息已成为研究热点,但也是难点。针对通信电台,提出了一种分选识别技术。该技术从电台物理层特性出发,对其辐射信号的细微特征进行K-means聚类以实现分选,分选的同时提取各个个体的特征属性值,未知信号通过与特征属性值相关运算实现个体识别。该技术无需先验知识,无需训练运算,通过实验验证,其可行、高效,易于工程实现。

关 键 词:电台分选识别  细微特征  K-means聚类  个体识别

Radio sorting and recognition technology based on K-means clustering for subtle features
YANG Liangliang.Radio sorting and recognition technology based on K-means clustering for subtle features[J].Telecommunication Engineering,2022,62(8).
Authors:YANG Liangliang
Affiliation:Southwest China Institute of Electronic Technology,Chengdu 610036,China
Abstract:Wireless communication equipment is increasing in modern battlefield,and accurate access to individual information has become a research focus,but it is also a difficult point.For communication radio,a sorting and identification technology is proposed.According to the characteristics of the radio physical layer,the technology carries out K-means clustering of the subtle characteristics of its radiation signal to achieve separation.At the same time,the individual characteristic attribute values are extracted.Finally,individual recognition is realized through related operation with the attribute values.The technical does not require prior knowledge or training calculation.Experiment results prove it is feasible,efficient and easy to implement.
Keywords:radio sorting and recognition  subtle characteristics  K-means clustering  individual recognition
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