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

• Autorzy: Stubberud P. A. , Stubberud A. R.
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

space vehicles; micro-inertial sensors; MEMS; accuracy; extended Kalman filter; micro-gyroscopes

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Systems Science
• Rocznik: 2009
• Tom: Vol. 35, no 2
• Strony: 59--65
• Opis fizyczny: Bibliogr. 6 poz., wykr.

Twórcy

autor

Stubberud P. A.

autor

Stubberud A. R.

• University of Nevada, Department of Electrical and Computer Engineering, Las Vegas, NV 89154-4026, USA,

Bibliografia

• [1] Stubberud A.R., Constrained Estimate of the State of a Time-Variable System, Proceedings of the Fourteenth International Conference on Systems Engineering, Coventry, 2000, pp. 513-518.
• [2] Stubberud A.R., A Validation of the Neural Extended Kalman Filter, Proceedings of the Eighteenth International Conference on Systems Engineering, Coventry, 2006, pp. 3-8.
• [3] Stubberud A.R., Santina M., Hosteller G.H., Digital Control System Design, Saunders College Publishing, New York, 1994.
• [4] Stubberud A.R., Stubberud P.A., Sequential State Estimates Subject to Equality Constraints, Proceedings of the 4th WSEAS Int. Conf. on Instrumentation, Measurement, Control, Circuits and Systems, DVD ROM, paper no. 484-324, Miami, 2004.
• [5] Stubberud A.R., Stubberud S.C., An Improved Constrained Nonlinear State Estimator for Target Tracking, Proceedings of the Fifteenth International Conference on Systems Science, Wroclaw, 2004, pp. 350-359.
• [6] Stubberud A.R., Yu X.-H., Signal Processing for Micro-Inertial Sensors, RTO Meeting Proceedings 44, Advances in Vehicle Systems Concepts and Integration, NATO Research and Technology Organization, Neuilly-Sur-Seine, France, 2000, B11-1-B11-7.