• DocumentCode
    174674
  • Title

    An effective unscented Kalman filter for state estimation of a gyro-free inertial measurement unit

  • Author

    Chaojun Liu ; Shuai Yu ; Shengzhi Zhang ; Xuebing Yuan ; Sheng Liu

  • Author_Institution
    Sch. of Mech. Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2014
  • fDate
    5-8 May 2014
  • Firstpage
    230
  • Lastpage
    235
  • Abstract
    This study reports a gyro-free inertial measurement unit (IMU) using solely four triaxial accelerometers. System equations and a configuration which is feasible for the gyro-free IMU design are presented. The propagation of accelerometer measurement errors is analyzed. An unscented Kalman filter (UKF) is proposed for state estimation. Simulation results show that the system state is robustly estimated by the proposed UKF. Furthermore, compared with the results of error analysis, the UKF provides effective error reductions on state estimation. The error of angular velocity estimation over full scale (FS) is about ±0.4%FS.
  • Keywords
    Kalman filters; accelerometers; error analysis; gyroscopes; inertial navigation; nonlinear filters; sensor fusion; FS; UKF; accelerometer measurement error propagation; angular velocity estimation; full scale; gyrofree IMU design; gyrofree inertial measurement unit; triaxial accelerometers; unscented Kalman filter; Acceleration; Accelerometers; Angular velocity; Force; State estimation; Vectors; accelerometer configuration; error analysis; gyro-free inertial measurement unit; state estimation; unscented Kalman filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Position, Location and Navigation Symposium - PLANS 2014, 2014 IEEE/ION
  • Conference_Location
    Monterey, CA
  • Print_ISBN
    978-1-4799-3319-8
  • Type

    conf

  • DOI
    10.1109/PLANS.2014.6851380
  • Filename
    6851380