In Use Parameter Estimation of Inertial Sensors by Detecting Multilevel Quasi-static States

  • Ashutosh Saxena
  • Gaurav Gupta
  • Vadim Gerasimov
  • Sébastien Ourselin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3684)


We present an autoadaptive algorithm for in-use parameter estimation of MEMS inertial accelerometers and gyros using multi-level quasi-static states for greater accuracy and reliability. Multi-level quasi-static states are detected robustly using data from both gyros and accelerometers. Proper estimation of time-varying sensor parameters allows us to develop a mixed-reality real-time hand-held orientation tracker with dynamic accuracy of less than 20. Existing methods like Kalman filters do not take time-varying nature of parameters into account, instead modelling the time-variation as higher values in noise covariance matrices; thus underestimating the sensor capabilities.


Inertial Sensor Orientation Error Triaxial Accelerometer Dynamic Accuracy Angular Rate Sensor 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ashutosh Saxena
    • 1
  • Gaurav Gupta
    • 2
  • Vadim Gerasimov
    • 3
  • Sébastien Ourselin
    • 2
  1. 1.Department of Electrical EngineeringStanford UniversityUSA
  2. 2.Autonomous Systems LaboratoryBioMedIA Lab, CSIRO ICT CentreEppingAustralia
  3. 3.Autonomous Systems LaboratoryCSIRO ICT CentreEppingAustralia

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