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Combining Numerous Uncorrelated MEMS Gyroscopes for Accuracy Improvement Based on an Optimal Kalman Filter

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5 Author(s)
Honglong Chang ; Micro and Nano Electromechanical Systems Laboratory, Northwestern Polytechnical University , Xi'an, China ; Liang Xue ; Chengyu Jiang ; Michael Kraft
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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/√Hz and a bias instability of 62°/h can be combined to form a virtual gyroscope with a noise density of 0.03°/s/√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.

Published in:

IEEE Transactions on Instrumentation and Measurement  (Volume:61 ,  Issue: 11 )