• DocumentCode
    106788
  • Title

    Integration of MEMS Inertial and Pressure Sensors for Vertical Trajectory Determination

  • Author

    Zihajehzadeh, Shaghayegh ; Tien Jung Lee ; Jung Keun Lee ; Hoskinson, Reynald ; Park, Edward J.

  • Author_Institution
    Sch. of Mechatron. Syst. Eng., Simon Fraser Univ., Surrey, BC, Canada
  • Volume
    64
  • Issue
    3
  • fYear
    2015
  • fDate
    Mar-15
  • Firstpage
    804
  • Lastpage
    814
  • Abstract
    Integration of a low-cost global positioning system (GPS) with a microelectromechanical system-based inertial measurement unit (MEMS-IMU) is a widely used method that takes advantage of the individual superiority of each system to get a more accurate and robust navigation performance. However, because of poor observations as well as multipath effects, the GPS has low accuracy in the vertical direction. As a result, the navigation accuracy even in an integrated GPS/MEMS-IMU system is more challenged in the vertical direction than the horizontal direction. To overcome this problem, this paper investigates the integration of a MEMS barometric pressure sensor with the MEMS-IMU for vertical position/velocity tracking without the GPS that has applications in sports. A cascaded two-step Kalman filter consisting of separate orientation and position/velocity subsystems is proposed for this integration. Slow human movements in addition to more rapid sport activities such as vertical and step-down jumps can be tracked using the proposed algorithm. The height-tracking performance is benchmarked against a reference camera-based motion-tracking system and an error analysis is performed. The experimental results show that the vertical trajectory tracking error is less than 28.1 cm. For the determination of jump vertical height/drop, the proposed algorithm has an error of less than 5.8 cm.
  • Keywords
    Global Positioning System; Kalman filters; atmospheric pressure; inertial navigation; microsensors; pressure sensors; GPS; MEMS barometric pressure sensor; MEMS inertial measurement unit; cascaded two-step Kalman filter; error analysis; height-tracking performance; low-cost global positioning sys- tem; multipath effects; navigation accuracy; slow human movements; vertical position/velocity tracking; vertical trajectory determination; Accelerometers; Global Positioning System; Micromechanical devices; Noise; Sensors; Trajectory; Vectors; Barometric pressure sensor; Kalman filter (KF); inertial measurement unit (IMU); inertial navigation system (INS); jump trajectory; microelectromechanical system (MEMS); sports; vertical trajectory; wearable technology; wearable technology.;
  • fLanguage
    English
  • Journal_Title
    Instrumentation and Measurement, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9456
  • Type

    jour

  • DOI
    10.1109/TIM.2014.2359813
  • Filename
    6922538