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Micromachines 2014, 5(4), 1034-1050; doi:10.3390/mi5041034

Analysis of Dynamic Performance of a Kalman Filter for Combining Multiple MEMS Gyroscopes

1
Xi'an Research Inst. of Hi-Tech, Hongqing Town, Xi'an 710025, China
2
MOE Key Laboratory of Micro and Nano Systems for Aerospace, Northwestern Polytechnical University, 127 Youyi West Road, Xi'an 710072, China
*
Author to whom correspondence should be addressed.
Received: 25 August 2014 / Revised: 14 October 2014 / Accepted: 31 October 2014 / Published: 7 November 2014
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Abstract

In this paper, the dynamic performance of a Kalman filter (KF) was analyzed, which is used to combine multiple measurements of a gyroscopes array to reduce the noise and improve the accuracy of the individual sensors. A principle for accuracy improvement by the KF was briefly presented to obtain an optimal estimate of input rate signal. In particular, the influences of some crucial factors on the KF dynamic performance were analyzed by simulations such as the factors input signal frequency, signal sampling, and KF filtering rate. Finally, a system that was comprised of a six-gyroscope array was designed and implemented to test the dynamic performance. Experimental results indicated that the 1σ error for the combined rate signal was reduced to about 0.2°/s in the constant rate test, which was a reduction by a factor of more than eight compared to the single gyroscope. The 1σ error was also reduced from 1.6°/s to 0.48°/s in the swing test. It showed that the estimated angular rate signal could well reflect the dynamic characteristic of the input signal in dynamic conditions. View Full-Text
Keywords: microelectromechanical systems (MEMS) gyroscope; array signal; filtering; dynamic performance; noise reduction microelectromechanical systems (MEMS) gyroscope; array signal; filtering; dynamic performance; noise reduction
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Xue, L.; Wang, L.; Xiong, T.; Jiang, C.; Yuan, W. Analysis of Dynamic Performance of a Kalman Filter for Combining Multiple MEMS Gyroscopes. Micromachines 2014, 5, 1034-1050.

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