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A New Type Double-Threshold Signal Detection Algorithm for Satellite Communication Systems Based on Stochastic Resonance Technology

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Abstract

In order to further improve the accurate detection signal, reduce interference between signals, this paper designs a new type of signal detection algorithm for satellite communication systems, using stochastic resonance technology improve the signal-to-noise ratio of the input signal, the signal by using energy detection, double threshold, accurate judgment. The first step in the conventional energy of double threshold detection, the second step into the energy detection method based on stochastic resonance detection process. The experimental results show that this algorithm under the condition of low SNR signals effectively detect, promoted the whole satellite communication system performance.

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Acknowledgement

This work is supported by Heilongjiang Natural Science Fund Project (F2015019, F2015017) (2017RAXXJ055), and Heilongjiang Provincial Postdoctoral Fund Project (LBH-Z16054).

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Authors and Affiliations

  1. Harbin Engineering University, Harbin, 150000, China

    Xiaolin Jiang & Ming Diao

  2. Heilongjiang University of Science and Technology, Harbin, 150000, China

    Xiaolin Jiang

Authors
  1. Xiaolin Jiang
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  2. Ming Diao
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Corresponding author

Correspondence to Xiaolin Jiang .

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Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Min Jia

  2. Harbin Institute of Technology, Harbin, China

    Qing Guo

  3. Harbin Institute of Technology, Harbin, China

    Weixiao Meng

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Jiang, X., Diao, M. (2019). A New Type Double-Threshold Signal Detection Algorithm for Satellite Communication Systems Based on Stochastic Resonance Technology. In: Jia, M., Guo, Q., Meng, W. (eds) Wireless and Satellite Systems. WiSATS 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 281. Springer, Cham. https://doi.org/10.1007/978-3-030-19156-6_25

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  • DOI: https://doi.org/10.1007/978-3-030-19156-6_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19155-9

  • Online ISBN: 978-3-030-19156-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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