Combining numerous uncorrelated MEMS gyroscopes for accuracy improvement based on an optimal Kalman filter

[en] In this paper, an approach to improve the accuracy of microelectromechanical systems (MEMS) gyroscopes by combining numerous uncorrelated gyroscopes is presented. A Kalman filter (KF) is used to fuse the output signals of several uncorrelated sensors. The relationship between the KF bandwidth and the angular rate input is quantitatively analyzed. A linear model is developed to choose suitable system parameters for a dynamic application of the concept. Simulation and experimental tests of a six-gyroscope array proved that the presented approach was effective to improve the MEMS gyroscope accuracy. The experimental results indicate that six identical gyroscopes with a noise density of 0.11°/s/$\surd$Hz and a bias instability of 62°/h can be combined to form a virtual gyroscope with a noise density of 0.03°/s/$\surd$Hz and a bias instability of 16.8°/h . The accuracy improvement is better than that of a simple averaging process of the individual sensors.

Disciplines :

Electrical & electronics engineering

Author, co-author :

Chang, Honglong

Xue, Liang

Jiang, Chengyu

Kraft, Michaël ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes microélectroniques intégrés

Yuan, Weizheng

Language :

English

Title :

Combining numerous uncorrelated MEMS gyroscopes for accuracy improvement based on an optimal Kalman filter

Publication date :

2012

Journal title :

IEEE Transactions on Instrumentation and Measurement

ISSN :

0018-9456

eISSN :

1557-9662

Publisher :

Institute of Electrical and Electronics Engineers, United States - New York

Volume :

Issue :

Pages :

3084-3093

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6214600

Available on ORBi :

since 26 March 2015

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