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New individual identification method of radiation source signal based on entropy feature and SVM
  • ISSN号:1005-9113
  • 期刊名称:Journal of Harbin Institute of Technology
  • 时间:2014
  • 页码:98-101
  • 分类:TN95[电子电信—信号与信息处理;电子电信—信息与通信工程] TP391.41[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]Department of Information and Communication Engineering, University of Harbin Engineering, Harbin 150001, China
  • 相关基金:Project(61301095)supported by the National Natural Science Foundation of China; Project(QC2012C070)supported by Heilongjiang Provincial Natural Science Foundation for the Youth,China; Projects(HEUCF130807,HEUCFZ1129)supported by the Fundamental Research Funds for the Central Universities of China
  • 相关项目:基于MIMO的多波段脉冲超宽带传输新方法与信道模型研究
中文摘要:

In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio(SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than-4 d B, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.

英文摘要:

In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio(SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than-4 d B, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.

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期刊信息
  • 《哈尔滨工业大学学报:英文版》
  • 主管单位:工业和信息化部
  • 主办单位:哈尔滨工业大学
  • 主编:
  • 地址:哈尔滨市西大直街92号136信箱
  • 邮编:150001
  • 邮箱:hitxuebao_e@HIT.edu.cn
  • 电话:0451-86414135
  • 国际标准刊号:ISSN:1005-9113
  • 国内统一刊号:ISSN:23-1378/T
  • 邮发代号:14-263
  • 获奖情况:
  • 2000年获黑龙江省科技期刊一等奖,2012年获科技类“2012中国国际影响力优秀学术期刊...
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  • 被引量:160