Noise reduction and estimation in multiple micro-electro-mechanical inertial systems

Adrian Waegli, Jan Skaloud, Stéphane Guerrier, Maria Eullia Parés, Ismael Colomina

Research output: Contribution to journalArticlepeer-review


This research studies the reduction and the estimation of the noise level within a redundant configuration of low-cost (MEMS-type) inertial measurement units (IMUs). Firstly, independent observations between units and sensors are assumed and the theoretical decrease in the system noise level is analyzed in an experiment with four MEMS-IMU triads. Then, more complex scenarios are presented in which the noise level can vary in time and for each sensor. A statistical method employed for studying the volatility of financial markets (GARCH) is adapted and tested for the usage with inertial data. This paper demonstrates experimentally and through simulations the benefit of direct noise estimation in redundant IMU setups.

Original languageEnglish (US)
Article number065201
JournalMeasurement Science and Technology
Issue number6
StatePublished - 2010
Externally publishedYes


  • ARMA
  • IMU
  • MEMS
  • Noise estimation
  • Redundancy

ASJC Scopus subject areas

  • Instrumentation
  • Engineering (miscellaneous)
  • Applied Mathematics


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