A Novel Special Emitter Identification Method Based on Improved Subclass Discriminant Analysis

摘要：

　　Radio frequency fingerprinting(RFF)is used to uniquely identify individual radios by exploiting the radio frequency characteristics.Often attributing to the phase ambiguity,the features of an emitter may split into several clusters,in this case,the traditional feature extraction methods,such as Linear Discriminant Analysis(LDA),Subclass Discriminant Analysis(SDA),lose efficacy.This paper investigates the problem of feature extraction and presents an improved SDA method.By modifying the clustering algorithm and replacing the sample covariance matrix with within-subclass scatter matrix,our method can achieve better performance.

关键词： special emitter identification radio frequency fingerprinting discriminant analysis Feature extraction pattern recognition

作者: Guiliang Wang Yuanling Huang

作者单位: Science and Technology on Blind Signal Processing Laboratory Chengdu,P.R.China

会议类型: 国际会议

会议名称: 2017 IEEE 2nd Advanced Information Technology,Electronic and Automation Control Conference(IAEAC 2017)(2017 IEEE 第2届先进信息技术、电子与自动化控制国际会议)

会议地点: 重庆

会议语种:英文

页码: 114-118

在线出版日期: 2017-03-25（万方平台首次上网日期，不代表论文的发表时间）