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Multi-Scale Fusion Algorithm for AUVs Integrated Navigation Systems

论文摘要

To deal with the low location accuracy issue of existing underwater navigation technologies in autonomous underwater vehicles（AUVs）,a distributed fusion algorithm which combines the model’s analysis method with a multi-scale transformation method is proposed for integrated navigation system based on AUV.First,integrated navigation system theory and system error sources are introduced in details.Secondly,a navigation systems observation equation on the original scale is decomposed into different scales by the discrete wavelet transform method,and noise reduction is performed by setting the wavelet de-noising threshold.At last,the dynamic equation and observation equations are fused on different scales by the wavelet transformation and Kalman filter.The results show that the proposed algorithm has smaller navigation error and higher navigation accuracy.

论文目录

  • 1 DVL/SINS Navigation System Model
  • 2 Multi-Scale Transformation Me-th-od
  •   2.1 Discrete wavelet transform analysis
  •   2.2 State and observation equation multi-scale transform
  •   2.3 Multi-scale transform noise reduction
  •   2.4 Ensemble Kalman filter
  • 3 Experiment Results
  • 4 Conclusion

    • 文章来源

    类型: 期刊论文

    作者: Yushan Sun,Fanyu Wu,Yuqi Wang,Guocheng Zhang,Bin Kong

    来源: Journal of Beijing Institute of Technology 2019年04期

    年度: 2019

    分类: 工程科技Ⅱ辑,信息科技

    专业: 船舶工业,电信技术

    单位: Science and Technology on Underwater Vehicle Laboratory,Harbin Engineering University,Key Laboratory of System Control and Information Processing,Shanghai Jiao Tong University,Wuhan Second Ship Design and Research Institute

    基金: Supported by the National Natural Science Foundation of China(51779057,51709061,51509057),the Equipment Pre-Research Project(41412030201),the National 863 High Technology Development Plan Project(2011AA09A106)

    分类号: TN967.2;U666.7;U674.941

    DOI: 10.15918/j.jbit1004-0579.18096

    页码: 725-730

    总页数: 6

    文件大小: 2983K

    下载量: 14

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