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International Conference in Communications, Signal Processing, and Systems

CSPS 2017: Communications, Signal Processing, and Systems pp 2552–2564Cite as

Target Recognition Based on 3-D Sparse Underwater Sonar Sensor Network

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

Abstract

Underwater target recognition is becoming a hot topic nowadays. In this paper, we propose a maximum likelihood automatic target recognition (ML-ATR) algorithm for both non-fluctuating and fluctuating targets. Theoretical analysis illustrates that our underwater ML-ATR method can tremendously reduce the number of physical sensors while maintain in a good performance. Simulations further validate these theoretical results.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, 76019, USA

    Hao Liang & Qilian Liang

Authors
  1. Hao Liang
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  2. Qilian Liang
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Corresponding author

Correspondence to Qilian Liang .

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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Cite this paper

Liang, H., Liang, Q. (2019). Target Recognition Based on 3-D Sparse Underwater Sonar Sensor Network. 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_310

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  • DOI: https://doi.org/10.1007/978-981-10-6571-2_310

  • Published:

  • 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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