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1 2009

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A signal processing technique for improving the accurancy of MEMS inertial sensors

Stubberud P. A., Stubberud A. R.

Systems Science

2009

Vol. 35, no 2

59-65

Navigation, guidance and control for small space vehicles requires inertial measurement sensors which are small, inexpensive, low power, reliable and accurate. Micro-inertial sensors, such as MEMS gyroscopes, can provide small, inexpensive, low power devices; however, the accuracy of these devices is insufficient for many space applications. Signal processing methods can be used to provide the necessary accuracy. The individual outputs of many nominally identical micro-sensors can be combined to generate a single accurate measurement. An extended Kalman filter (EKF) which includes the dynamics of every sensor can be used for such a combination; however, the "curse of dimensionality" limits the number of sensors which can be used. In this paper, a new EKF technique for combining many sensors is proposed which, using a common nominal model for the micro-sensors and a single EKF with the state dimension of a single sensor, has accuracy comparable to the high dimensional EKF and is significantly more accurate than a single sensor. A simulation using the mathematical model of an existing micro-gyroscope was performed to compare the single EKF method to the multiple EKF method and the results presented.