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Improved filter estimation method applied in zero velocity update for SINS

  • Yueyang Ben*
  • , Guisheng Yin
  • , Wei Gao
  • , Feng Sun
  • *Corresponding author for this work
  • College of Computer Science and Technology, Harbin Engineering University
  • Harbin Engineering University

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

Abstract

Zero Velocity Update (ZUPT) utilizes the zero velocity condition for stationary Strapdown Inertial Navigation System (SINS), executes navigation errors estimation and emendation to control SINS position growth. The improved filter estimation ZUPT is proposed in this paper. Two technologies, separate-bias kalman filter and yaw error rapid estimation, are applied in the proposed method. Separate-bias kalman filter solve the divergence problem for setting a mass of kalman filter state variances. And the yaw error rapid estimation can calculate the unobservable yaw error in periodic ZUPT. Simulation results show that the estimations of attitude errors, yaw error and position errors converge to the right values quickly in the proposed ZUPT, and the position accuracy is improved effectively compared to the conventional one.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Pages3375-3380
Number of pages6
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009 - Changchun, China
Duration: 9 Aug 200912 Aug 2009

Publication series

Name2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009

Conference

Conference2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Country/TerritoryChina
CityChangchun
Period9/08/0912/08/09

Keywords

  • Kalman filter
  • SINS
  • Separate-bias
  • ZUPT

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