• DocumentCode
    581868
  • Title

    Automatic calibration and in-motion alignment of an odometer-aided INS

  • Author

    Qingzhe, Wang ; Mengyin, Fu ; Xuan, Xiao ; Zhihong, Deng

  • Author_Institution
    Sch. of Autom., Beijing Inst. of Technol., Beijing, China
  • fYear
    2012
  • fDate
    25-27 July 2012
  • Firstpage
    2024
  • Lastpage
    2028
  • Abstract
    In-motion alignment problem has been regarded as a challenging problem for years in the extensive study on inertial navigation systems (INS´s). In this contribution, the problem of odometer-aided in-motion alignment is investigated, where the nonholonomic constraints are efficiently employed in the designed Kalman filtering process with the measured data provided by a calibrated odometer. As the application of odometer under nonholonomic constraints requires the INS body axes to be well aligned with the vehicle body frame (VBF), INS-to-VBF alignment and calibration of odometer´s scale factor are implemented in the INS/Odometer integration. To the end of in-motion alignment, the system and measurement equations for INS/Odometer integration are derived to construct a Kalman filter, which is used to process the integrated velocity information and then to obtain estimates of both odometer error states and INS error states. With these parameter estimates, the odometer outputs can be calibrated properly, which makes the in-motion alignment implementable and practical. The effectiveness of the proposed method is tested through ground based navigation experiments.
  • Keywords
    Kalman filters; calibration; distance measurement; inertial navigation; inertial systems; measurement errors; motion measurement; state estimation; INS error state estimation; INS-to-VBF alignment; Kalman filtering process; automatic odometer scale factor calibration; in-motion alignment problem; inertial navigation system; integrated velocity information; measurement equation; nonholonomic constraint; odometer error state estimation; odometer-aided INS; parameter estimation; vehicle body frame; Accuracy; Equations; Kalman filters; Mathematical model; Measurement uncertainty; Navigation; Vehicles; INS-to-VBF Alignment; In-motion Alignment; Inertial Navigation System; Kalman Filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2012 31st Chinese
  • Conference_Location
    Hefei
  • ISSN
    1934-1768
  • Print_ISBN
    978-1-4673-2581-3
  • Type

    conf

  • Filename
    6390257