Automatic Recognition Method of Digital Communication Signal Under Strong Electromagnetic Interference

Authors

  • Hao Yang School of Information Engineering, Zhengzhou Institute of Technology, Zhengzhou 450044, China
  • Chen Zhang College of Rail Transit, Henan Communication Vocational Technology College, Zhengzhou 450006, China
  • Bingxu Zhao The 713th Research Institute of China Shipbuilding Industry Corporation, Zhengzhou 450006, China

Abstract

In the current automatic recognition method of digital communication signals based on entropy features, approximate entropy and norm entropy constitute an eigenvector to achieve signal recognition. Without signal filtering, it takes longer time for feature extraction, the recognition accuracy of signal is low, and the energy consumption of signal recognition is high. An automatic method for recognising digital communication signals based on complex features is proposed in this paper. The median filter and a posteriori Wiener filter are used to filter the digital communication signals in the presence of strong electromagnetic interference. The signal denoising result is applied to enhance the digital communication signal, achieving further separation of signals. Meanwhile, the dimensionality of the signal is reduced and the result of this dimensionality reduction is substituted into
digital communication signal recognition, and the automatic recognition of digital communication signals under strong electromagnetic interference is achieved. Experimental results show that the proposed method can enhance the signal filtering effect, improve the efficiency and accuracy of signal recognition, reduce the energy consumption of recognition, and has strong reliability.

Keywords: Strong electromagnetic interference; digital communication signals; automatic identification

Cite As

H. Yang, C. Zheng, B. Zhao, "Automatic Recognition Method of Digital Communication Signal Under
Strong Electromagnetic Interference", Engineering Intelligent Systems, vol. 29 no. 4, pp. 217-223, 2021.




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Published

2021-07-01

Issue

Vol. 29 No. 4 (2021): International Journal of Engineering Intelligent Systems

Section

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