A neural network hybrid filter used in strap-down north-finder

Yu Feng Zhang*, Jia Bin Chen, Chao Zhe Zhu, Long Zhang, Xiao Rui Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Introduces the principle of strap-down north-finder and studies the question of improving the precision of north-finder when under a random disturbance. Neural network has the ability of simulating non-linear curves. It can thus simulate the output of the north-finder. The paper shows a design for a hybrid filter that combines neural network and low-pass filter. When the north-finder meets with a random disturbance, the output of neural network will replace the output of the north-finder. The result of filtering the real-data that has random distrubance shows that this hybrid filter can reduce the influence of random disturbance efficiently.

Original languageEnglish
Pages (from-to)330-333
Number of pages4
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume21
Issue number3
Publication statusPublished - 2001

Keywords

  • Integrated filter
  • Neural network
  • North-finder

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Zhang, Y. F., Chen, J. B., Zhu, C. Z., Zhang, L., & Wang, X. R. (2001). A neural network hybrid filter used in strap-down north-finder. Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 21(3), 330-333.