A new invariant extended Kalman filter based initial alignment method of SINS under large misalignment angle

Hongpo Fu, Yongmei Cheng, Tianyi Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

For the initial alignment of strapdown inertial navigation system (SINS) under the condition of large azimuth misalignment, a high-precision and fast initial alignment method is proposed. Firstly, in the Lie group space, the system matrix F and the measurement matrix H, which are relatively independent of the state estimate, are derived, and the invariant extended Kalman filter (INEKF) architecture. The INEKF not only eliminates the influence of the current state estimation error on the system matrix F and the measurement matrix H, but also suppresses the positive feedback and inconsistency problems that occur in the state update process of EKF. Then, the SINS initial alignment model is established based on INEKF. Finally, simulation results show that this method can effectively improve the speed and accuracy of the initial alignment, especially under the condition of a large misalignment angle, the alignment speed and accuracy are also greatly improved.

Original languageEnglish
Title of host publicationProceeding - 2021 China Automation Congress, CAC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages57-62
Number of pages6
ISBN (Electronic)9781665426473
DOIs
StatePublished - 2021
Event2021 China Automation Congress, CAC 2021 - Beijing, China
Duration: 22 Oct 202124 Oct 2021

Publication series

NameProceeding - 2021 China Automation Congress, CAC 2021

Conference

Conference2021 China Automation Congress, CAC 2021
Country/TerritoryChina
CityBeijing
Period22/10/2124/10/21

Keywords

  • Initial alignment
  • Invariant extended Kalman filter
  • Large misalignment angle
  • Strapdown inertial navigation system

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