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Performance comparison of two filtering approaches for INS rapid transfer alignment

  • Gao Wei*
  • , Ben Yueyang
  • , Sun Feng
  • , Xu Bo
  • *Corresponding author for this work
  • Harbin Engineering University

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

Abstract

This paper presents a velocity matching scheme for rapid transfer alignment of INS. Velocity matching algorithm is known as one of the best matching algorithm of SINS in-motion alignment since it can achieve high alignment accuracy without lengthy time requirement. We try to find a more excellent filter than the traditional kalman filter in this paper. Firstly the mathematical model of velocity matching is presented, and the kalman filter and robust filter formulations are introduced. Then it analyses the observability of various states in velocity matching scheme. This paper mainly focuses on the misalignment estimated accuracy and convergence speed of the proposed algorithm. In order to validate the effect of the velocity matching algorithm, three-axis sway model simulation based on 10 dimensions states and S dimensions states is carried out. The results of simulation suggest that the estimating accuracy of kalman filter is equivalent with that of robust filter, but convergence rate of robust filter are much better than that of kalman filter. Furthermore, reduced order model is adaptable for the practical INS alignment considering the computational complexity of the presented velocity matching algorithm.

Original languageEnglish
Title of host publicationProceedings of the 2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007
Pages1956-1961
Number of pages6
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007 - Harbin, China
Duration: 5 Aug 20078 Aug 2007

Publication series

NameProceedings of the 2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007

Conference

Conference2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007
Country/TerritoryChina
CityHarbin
Period5/08/078/08/07

Keywords

  • Kalman filter
  • Robust filter
  • Transfer alignment

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