Proceedings of the 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)

Attitude Estimation Based on Modified Two-stage EKF

Authors
Peinan Wang, Zhiqiang Wang, Qing Zhu
Corresponding Author
Peinan Wang
Available Online March 2017.
DOI
https://doi.org/10.2991/msam-17.2017.30How to use a DOI?
Keywords
extended kalman filter; motion capture; attitude estimation
Abstract
In this paper, an attitude estimation algorithm based on modified two-stage Extended Kalman Filter (EKF) is presented to improve the accuracy of attitude estimation based on Micro Electro-Mechanical System (MEMS) motion capture technology. Firstly, a two-stage EKF is presented to replace the conventional EKF, to reduce the computational complexity and computing time. Secondly, the normalized quaternion model is applied instead of Euler Angle model to reduce the calculation error of attitude estimation. Finally, the automatic error compensation realized through constructing the acceleration error covariance operator to adjust error covariance matrix according to the measurement values of the acceleration. The experiment result shows that the proposed method can significantly reduce the computational complexity and the size of universal joint deadlocks and linear acceleration effect on the attitude estimation.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2017
ISBN
978-94-6252-324-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/msam-17.2017.30How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Peinan Wang
AU  - Zhiqiang Wang
AU  - Qing Zhu
PY  - 2017/03
DA  - 2017/03
TI  - Attitude Estimation Based on Modified Two-stage EKF
BT  - 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
PB  - Atlantis Press
SP  - 134
EP  - 138
SN  - 1951-6851
UR  - https://doi.org/10.2991/msam-17.2017.30
DO  - https://doi.org/10.2991/msam-17.2017.30
ID  - Wang2017/03
ER  -