@inproceedings{028c1e9488724addbaf737a8bbbe93bb,
title = "Research on the calibration method of MEMS accelerometer based on recursive least squares",
abstract = "The calibration of MEMS accelerometer system error parameters need a large amount of sampling point. In order to reduce the sampling points, this paper proposes a calibration method based on recursive least square (RLS) estimation. First establish the error model of accelerometer and then carried out the simulation experiment under the condition of considering external noise. The results show that compared with the traditional calibration method, this calibration method has higher calibration accuracy and reduces the calibration time. The experimental results show that the proposed method has certain engineering value.",
keywords = "Error calibration, MEMS accelerometer, Recursive least square estimation",
author = "Zhaoyi Chen and Huaijian Li and Xiaojing Du and Junliang Yan",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 15th IEEE International Conference on Mechatronics and Automation, ICMA 2018 ; Conference date: 05-08-2018 Through 08-08-2018",
year = "2018",
month = oct,
day = "5",
doi = "10.1109/ICMA.2018.8484627",
language = "English",
series = "Proceedings of 2018 IEEE International Conference on Mechatronics and Automation, ICMA 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "533--538",
booktitle = "Proceedings of 2018 IEEE International Conference on Mechatronics and Automation, ICMA 2018",
address = "United States",
}