Attitude Estimation Based on Modified Two-stage EKF

DOI

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.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 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  - 10.2991/msam-17.2017.30
ID  - Wang2017/03
ER  -