Research on MIMU Online Calibration Method Based on Multi-information Source

Junliang Yan, Xiaojing Du, Huaijian Li

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

1 Citation (Scopus)

Abstract

An online filtering calibration scheme was designed. According to the MIMU error model, the error parameters to be calibrated were incorporated into the system state vector to construct the filtering estimation state equation. On the basis of Kalman filter, a calibration observation scheme based on GPS and altimeter is designed. Aiming at the dynamic characteristics of error parameters to be calibrated, a stepwise estimation method is designed to reduce the computation time. Simulation results show that the design is reasonable.

Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages699-703
Number of pages5
ISBN (Electronic)9781728137926
DOIs
Publication statusPublished - Oct 2019
Event2019 IEEE International Conference on Unmanned Systems, ICUS 2019 - Beijing, China
Duration: 17 Oct 201919 Oct 2019

Publication series

NameProceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019

Conference

Conference2019 IEEE International Conference on Unmanned Systems, ICUS 2019
Country/TerritoryChina
CityBeijing
Period17/10/1919/10/19

Keywords

  • Kalman Filter
  • Multi-information Fusion
  • Online Calibration
  • SINS
  • Stepwise Estimation

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