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

Honglong Chang, Liang Xue, Chengyu Jiang, Michael Kraft, Weizheng Yuan

科研成果: 期刊稿件文章同行评审

69 引用 (Scopus)

摘要

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°/h and a bias instability of 62°/s can be combined to form a virtual gyroscope with a noise density of 0.03°/h and a bias instability of 16.8°/s. The accuracy improvement is better than that of a simple averaging process of the individual sensors.

源语言英语
文章编号6214600
页(从-至)3084-3093
页数10
期刊IEEE Transactions on Instrumentation and Measurement
61
11
DOI
出版状态已出版 - 2012

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