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Using AKF-PSR to Compensate Random Drift Errors of Low-Cost MEMS Gyroscopes

Xiao, Chunsheng and Zhu, Qingyuan and Hu, Huosheng and Zhang, Xiaoyu and Chen, Xuanwei and Song, Xinyi (2019) 'Using AKF-PSR to Compensate Random Drift Errors of Low-Cost MEMS Gyroscopes.' IEEE Sensors Journal, 19 (16). 6802 - 6810. ISSN 1530-437X

IEEE-SJ-V19-N16-2019-6802-6810.pdf - Accepted Version

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The random drift of a micro-electromechanical system (MEMS) gyroscope seriously affects its measurement accuracy. To model and compensate its random drift, the time series analysis method has widely been deployed, which, however, requires a large amount of data for pre-processing analysis and is unsuitable for real-time applications. This paper proposes a new random drift compensation method based on the adaptive Kalman filter (AKF) and phase space reconstruction (PSR). AKF is first designed to compensate the random drift of the low-cost MEMS gyroscope. The phase variables are then used as phase vectors via PSR. Experiments show that the proposed AKF-PSR method can effectively compensate the random drift of the gyroscope, and the standard deviation is reduced by half.

Item Type: Article
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 06 Jul 2021 11:34
Last Modified: 06 Jul 2021 11:34

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