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A Ship Tracking Algorithm of Harbor Channel Based on Orthogonal Particles Filter

  • Lei Xiao
  • Hui-Gang Wang
  • Mian-Lu Zou
  • Zhong-Yi Hu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 528)

Abstract

This paper, employing Bayes state estimation, proposes a ship tracking algorithm of harbor channel based on orthogonal particle filter. (1) The dynamic model fully takes speed of state change into consideration during the movement of target ship, to improve the problem that the existing correlation algorithms have poor adaptability to the target ship tracking of the complex mode. (2) The proposed algorithm reorganizes and estimates particles by using orthogonal particles arrays, which can avoid particles degradation problems caused by resampling. Experimental results demonstrate that our algorithm outperforms other algorithms.

Keywords

Ship tracking Bayes state estimation Orthogonal particles filter 

Notes

Acknowledgements

The authors acknowledge the financial supported by Zhejiang Provincial Natural Science Foundation of China (project No.: LZ15F030002, LY16F020022). The author is grateful to the anonymous referee for the careful checking of the details of this paper and for helpful comments and constructive criticism.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Lei Xiao
    • 1
  • Hui-Gang Wang
    • 1
  • Mian-Lu Zou
    • 2
  • Zhong-Yi Hu
    • 2
  1. 1.School of Marine Science and TechnologyNorthwestern Polytechnical UniversityXi’anChina
  2. 2.Intelligent Information Systems Institute, Wenzhou UniversityWenzhouChina

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