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RBF Neural Network-Based Temperature Error Compensation for Fiber Optic Gyroscopes

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Communications, Signal Processing, and Systems (CSPS 2020)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 654))

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Abstract

A temperature error compensation scheme for fiber optic gyroscope (FOG) based on radial basis function (RBF) neural network is proposed in this paper. By using the data preprocessing and orthogonal least square (OLS) learning method, the training performance of the network is improved and the over-fitting of the network is prevented. The experimental results illustrate that the proposed method has a 15–40% performance improvement compared with the conventional linear regression model.

Wei Cai created the first stable version of this paper and first draft of this paper

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References

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Author information

Authors and Affiliations

  1. China Academy of Electronics and Information Technology, Beijing, China

    Wei Cai, Jianyang Wang, Wenhui Hao, Yanguo Zhou & Yiming Liu

  2. National Engineering Laboratory for Public Safety Risk Perception and Control By Big Data, Beijing, China

    Jianyang Wang, Yanguo Zhou & Yiming Liu

Authors
  1. Wei Cai
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  2. Jianyang Wang
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  3. Wenhui Hao
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  4. Yanguo Zhou
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  5. Yiming Liu
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Corresponding author

Correspondence to Wei Cai .

Editor information

Editors and Affiliations

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

    Qilian Liang

  2. Tianjin Normal University, Tianjin, China

    Wei Wang

  3. Dalian University of Technology, Dalian, China

    Xin Liu

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

    Zhenyu Na

  5. Huazhong Agricultural University, Wuhan, China

    Xiaoxia Li

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

    Baoju Zhang

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© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Cite this paper

Cai, W., Wang, J., Hao, W., Zhou, Y., Liu, Y. (2021). RBF Neural Network-Based Temperature Error Compensation for Fiber Optic Gyroscopes. In: Liang, Q., Wang, W., Liu, X., Na, Z., Li, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2020. Lecture Notes in Electrical Engineering, vol 654. Springer, Singapore. https://doi.org/10.1007/978-981-15-8411-4_214

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  • DOI: https://doi.org/10.1007/978-981-15-8411-4_214

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-8410-7

  • Online ISBN: 978-981-15-8411-4

  • eBook Packages: EngineeringEngineering (R0)

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