Please submit manuscripts in either of the following two submission systems

    ScholarOne Manuscripts

  • ScholarOne
  • 勤云稿件系统

  • 登录

Search by Issue

  • 2024 Vol.31
  • 2023 Vol.30
  • 2022 Vol.29
  • 2021 Vol.28
  • 2020 Vol.27
  • 2019 Vol.26
  • 2018 Vol.25
  • 2017 Vol.24
  • 2016 vol.23
  • 2015 vol.22
  • 2014 vol.21
  • 2013 vol.20
  • 2012 vol.19
  • 2011 vol.18
  • 2010 vol.17
  • 2009 vol.16
  • No.1
  • No.2

Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

期刊网站二维码
微信公众号二维码
Related citation:Yun Lin,Xiao-Chun Xu,Zi-Cheng Wang.New Individual Identification Method of Radiation Source Signal Based on Entropy Feature and SVM[J].Journal of Harbin Institute Of Technology(New Series),2014,21(1):98-101.DOI:10.11916/j.issn.1005-9113.2014.01.014.
【Print】   【HTML】   【PDF download】   View/Add Comment  Download reader   Close
←Previous|Next→ Back Issue    Advanced Search
This paper has been: browsed 1253times   downloaded 983times 本文二维码信息
码上扫一扫!
Shared by: Wechat More
New Individual Identification Method of Radiation Source Signal Based on Entropy Feature and SVM
Author NameAffiliation
Yun Lin College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 
Xiao-Chun Xu College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 
Zi-Cheng Wang College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 
Abstract:
In this paper, according to the defect of methods which have low identification rate in low SNR, a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly, based on the theory of multi-resolution wavelet analysis, the wavelet power spectrum of non-cooperative signal can be gotten. Secondly, according to the information entropy theory, the wavelet power spectrum entropy is defined in this paper. Therefore, the database of signal’s wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally, the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual’s identification rate in low SNR, when the SNR is greater than 4 dB, the identification rate can reach 100%. Under unstable SNR conditions, when the range of SNR is between 0 dB and 24 dB, the average identification rate is more than 92.67%. Therefore, this method has a great application value in the complex electromagnetic environment.
Key words:  radiation source individual identification  wavelet power spectrum  information entropy  support vector machine
DOI:10.11916/j.issn.1005-9113.2014.01.014
Clc Number:TN911.6
Fund:

LINKS