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Phantom Track Identification for Radar Network Based on Multi-feature Fusion

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Communications, Signal Processing, and Systems (CSPS 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 463))

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Abstract

To combat against surveillance radar network, the electronic countermeasure scheme of phantom track is employed by the cooperation of multiple electronic combat air vehicles. A modified method is presented to enhance the phantom tracks identification performance for radar network in this paper. The temporal-spatial information fusion trick is applied based on Dempster-Shafer evidence theory. The features of range-angle measure errors and power amplifier distortion are analyzed to identify the phantom track. Simulation results prove that the proposed method is feasible and capable of identifying the phantom track accurately.

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Notes

  1. 1.

    For more detail about Kalman filter theory, check relevant books including Ref. [2].

References

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Author information

Authors and Affiliations

  1. School of Electronic Engineering, University of Electronic Science and Technology of China, Qingshuihe Campus: No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, China

    Yuan Zhao, Ahmed Abdalla Ali & Bin Tang

Authors
  1. Yuan Zhao
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  2. Ahmed Abdalla Ali
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  3. Bin Tang
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Corresponding author

Correspondence to Yuan Zhao .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, Texas, USA

    Qilian Liang

  2. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Jiasong Mu

  3. Harbin Institute of Technology, Harbin, Heilongjiang, China

    Min Jia

  4. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Xuhong Feng

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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© 2019 Springer Nature Singapore Pte Ltd.

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Zhao, Y., Ali, A.A., Tang, B. (2019). Phantom Track Identification for Radar Network Based on Multi-feature Fusion. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_332

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  • DOI: https://doi.org/10.1007/978-981-10-6571-2_332

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6570-5

  • Online ISBN: 978-981-10-6571-2

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