[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
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