An Improved Particle Filter Based on Gravity Measurement Feature in Gravity-Aided Inertial Navigation System

Shengwu Zhao, Xuan Xiao*, Yu Wang, Zhihong Deng

*Corresponding author for this work

Research output: Contribution to journalJournal Articlepeer-review

20 Citations (Scopus)

Abstract

The existing gravity matching algorithms are affected by the initial position error of the inertial navigation system (INS), the gravity measurement error, and the similarity of the gravity background map. Aiming at the above problems, an improved particle filter based on the gravity measurement feature (IPFBGMF) is proposed in this article. In the IPFBGMF, both the value and change characteristic of gravity measurements are considered, and a novel position acquisition method based on the gravity measurement feature is proposed, which can reduce the influence of the initial position error of INS. In addition, a new concept called direction measurement using the heading angle of INS is proposed to optimize the weight of particles in the PF. The PF with direction measurement can reduce the influence of the gravity measurement error and the similarity of the gravity background map. Furthermore, the robustness of the improved PF with the precise position is proven. Finally, a navigation strategy is designed to apply the proposed algorithms. Simulations show that IPFBGMF has the highest positioning accuracy compared with the traditional gravity matching algorithms.

Original languageEnglish
Pages (from-to)1423-1435
Number of pages13
JournalIEEE Sensors Journal
Volume23
Issue number2
DOIs
Publication statusPublished - 15 Jan 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2001-2012 IEEE.

Keywords

  • Extreme value
  • gravity measurement feature
  • gravity-aided inertial navigation system (GAINS)
  • particle filter (PF)
  • underwater navigation

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