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Ship Fuzzy Recognition Based on Superstructure with Maximum Membership Rule

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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

The Automatic Target Recognition (ATR) of ship targets based on high resolution Inverse Synthetic Aperture Radar (ISAR) images has a good prospect of marine environmental protection, monitoring and traffic management. In this letter, a novel ship classification technique is proposed based on the ship superstructure by using the fuzzy recognition method. An improved segmentation algorithm of the ship silhouette is applied to obtain the segment comparative mean (SCM) feature. The SCM is used to calculate the target’s membership of each class and eventually the maximum membership rule is applied to determine the target’s class. The experimental results of applying the technique on real ISAR data demonstrate the effectiveness of the proposed approach.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under grant 61622107 and 61471149.

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Authors and Affiliations

  1. Research Institute of Electronic Engineering Technology, Harbin Institute of Technology, Harbin, 150001, China

    Yong Wang & Pengkai Zhu

Authors
  1. Yong Wang
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  2. Pengkai Zhu
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Corresponding author

Correspondence to Yong Wang .

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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Wang, Y., Zhu, P. (2019). Ship Fuzzy Recognition Based on Superstructure with Maximum Membership Rule. 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_249

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  • DOI: https://doi.org/10.1007/978-981-10-6571-2_249

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6570-5

  • Online ISBN: 978-981-10-6571-2

  • eBook Packages: EngineeringEngineering (R0)

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