Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (22): 223-226.

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Individual frequency-hopping radio identification method based on transient characteristics of frequency domain

GU Chenhui1, WANG Lunwen1,2   

  1. 1.309 Research Division of Electronic Engineering Institute, Hefei 230037, China
    2.Science and Technology on Communication Information Security Control Laboratory, Jiaxing, Zhejiang 314033, China
  • Online:2013-11-15 Published:2013-11-15

基于频域瞬时特征的跳频电台个体识别方法

顾晨辉1,王伦文1,2   

  1. 1.电子工程学院 309室,合肥 230037
    2.通信信息控制和安全技术重点实验室,浙江 嘉兴 314033

Abstract: The radio communication signals usually turn out to be some fine character differences. In this paper, a method based on the box-counting dimensions and the maximal Lyapunov exponents of the individual FH radio is presented according to the fine character differences. Firstly, the transient frequency of the FH signals is extracted based on the improved Prony algorithm. Secondly, the transient characteristics including the maximal Lyapunov exponents and the box dimensions are computed. Finally, individual identification of the different FH radio based on the method of the Constructive Neural Network is realized. The experimental results have shown that this method is efficiency.

Key words: frequency-hopping radio, fine character, maximal Lyapunov exponent, box-counting dimension

摘要: 通信电台发射的信号通常表现出一定的细微特征差异,针对这种细微特征差异,提出了基于最大Lyapunov指数和盒维数的跳频电台个体识别方法。基于改进的Prony算法,提取样本信号跳变时刻的瞬时频率,分离并定量计算其最大Lyapunov指数和盒维数等瞬时特征,采用基于构造型神经网络的分类方法实现不同跳频电台的个体识别。实际数据的实验结果验证了算法的有效性。

关键词: 跳频电台, 细微特征, 最大Lyapunov指数, 盒维数