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Sensors 2012, 12(2), 1720-1737; doi:10.3390/s120201720
Article

Signal Processing of MEMS Gyroscope Arrays to Improve Accuracy Using a 1st Order Markov for Rate Signal Modeling

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Received: 30 December 2011; in revised form: 1 February 2012 / Accepted: 2 February 2012 / Published: 7 February 2012
(This article belongs to the Special Issue Modeling, Testing and Reliability Issues in MEMS Engineering 2011)
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Abstract: This paper presents a signal processing technique to improve angular rate accuracy of the gyroscope by combining the outputs of an array of MEMS gyroscope. A mathematical model for the accuracy improvement was described and a Kalman filter (KF) was designed to obtain optimal rate estimates. Especially, the rate signal was modeled by a first-order Markov process instead of a random walk to improve overall performance. The accuracy of the combined rate signal and affecting factors were analyzed using a steady-state covariance. A system comprising a six-gyroscope array was developed to test the presented KF. Experimental tests proved that the presented model was effective at improving the gyroscope accuracy. The experimental results indicated that six identical gyroscopes with an ARW noise of 6.2 °/√h and a bias drift of 54.14 °/h could be combined into a rate signal with an ARW noise of 1.8 °/√h and a bias drift of 16.3 °/h, while the estimated rate signal by the random walk model has an ARW noise of 2.4 °/√h and a bias drift of 20.6 °/h. It revealed that both models could improve the angular rate accuracy and have a similar performance in static condition. In dynamic condition, the test results showed that the first-order Markov process model could reduce the dynamic errors 20% more than the random walk model.
Keywords: MEMS gyroscope array; Kalman filter; first-order Markov process; rate accuracy improvement MEMS gyroscope array; Kalman filter; first-order Markov process; rate accuracy improvement
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.

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MDPI and ACS Style

Jiang, C.; Xue, L.; Chang, H.; Yuan, G.; Yuan, W. Signal Processing of MEMS Gyroscope Arrays to Improve Accuracy Using a 1st Order Markov for Rate Signal Modeling. Sensors 2012, 12, 1720-1737.

AMA Style

Jiang C, Xue L, Chang H, Yuan G, Yuan W. Signal Processing of MEMS Gyroscope Arrays to Improve Accuracy Using a 1st Order Markov for Rate Signal Modeling. Sensors. 2012; 12(2):1720-1737.

Chicago/Turabian Style

Jiang, Chengyu; Xue, Liang; Chang, Honglong; Yuan, Guangmin; Yuan, Weizheng. 2012. "Signal Processing of MEMS Gyroscope Arrays to Improve Accuracy Using a 1st Order Markov for Rate Signal Modeling." Sensors 12, no. 2: 1720-1737.



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