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Doppler Weather Radar Network Joint Observation and Reflectivity Data Mosaic

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Communications, Signal Processing, and Systems (CSPS 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 571))

Abstract

This paper realized the interpolation and three-dimensional mosaic of Doppler weather radar data. Currently, the Adaptive Barnes interpolation method is generally recognized as an effective algorithm for weather radar. The smoothing scheme of this algorithm are improved to keep good characteristics of the raw volume data. Compared with the commonly used interpolation methods, the improved smoothing scheme of the Adaptive Barnes interpolation can get better CAPPI data without over-smoothing effect.

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Author information

Authors and Affiliations

  1. Chengdu University of Information Technology, Chengdu, 610225, Sichuan, China

    Qutie Jiela, Haijiang Wang, Jiaoyang He & Debin Su

Authors
  1. Qutie Jiela
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  2. Haijiang Wang
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  3. Jiaoyang He
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  4. Debin Su
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Corresponding author

Correspondence to Haijiang Wang .

Editor information

Editors and Affiliations

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

    Qilian Liang

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

    Wei Wang

  3. School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, China

    Xin Liu

  4. School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning, China

    Zhenyu Na

  5. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China

    Min Jia

  6. College of Physical and Electronic Information, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Jiela, Q., Wang, H., He, J., Su, D. (2020). Doppler Weather Radar Network Joint Observation and Reflectivity Data Mosaic. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_263

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  • DOI: https://doi.org/10.1007/978-981-13-9409-6_263

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9408-9

  • Online ISBN: 978-981-13-9409-6

  • eBook Packages: EngineeringEngineering (R0)

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