Autocalibration of MEMS Accelerometers

  • Iuri Frosio
  • Federico Pedersini
  • N. Alberto Borghese
Part of the Microsystems book series (MICT, volume 23)


In this chapter, we analyze the critical aspects of the widely diffused calibration and autocalibration procedures for MEMS accelerometers. After providing a review of the main applications of this kind of sensors, we introduce the different sensor models proposed in literature, highlighting the role of the axis misalignments in the sensor sensitivity matrix. We derive a principled noise model and discuss how noise affects the norm of the measured acceleration vector. Since autocalibration procedures are based on the assumption that the norm of the measured acceleration vector, in static condition, equals the gravity acceleration, we introduce the international gravity formula, which provides a reliable estimate of the gravity acceleration as a function of the local latitude and altitude. We derive then the autocalibration procedure in the context of maximum likelihood estimate and we provide examples of calibrations. For each calibrated sensor, we also illustrate how to derive the accuracy on the estimated parameters through the covariance analysis and how to compute the angles between the sensing axes of the sensor. In the conclusion, we summarize the main aspects involved in the autocalibration of MEMS accelerometers.


Calibration Procedure Sensor Model Acceleration Vector Lower Triangular Matrix Sensitivity Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Iuri Frosio
    • 1
  • Federico Pedersini
    • 1
  • N. Alberto Borghese
    • 1
  1. 1.Computer Science DepartmentUniversity of MilanMilanoItaly

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