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Journal of Sensors
Volume 2017 (2017), Article ID 8542153, 12 pages
Research Article

Novel MARG-Sensor Orientation Estimation Algorithm Using Fast Kalman Filter

1School of Educational Software, Guangzhou University, Guangzhou, China
2School of Automation, University of Electronic Science and Technology of China, Chengdu, China
3Chengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu, China

Correspondence should be addressed to Jin Wu; moc.liamtoh@ctseu_uw_nij

Received 8 February 2017; Accepted 16 May 2017; Published 24 September 2017

Academic Editor: Calogero M. Oddo

Copyright © 2017 Siwen Guo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Orientation estimation from magnetic, angular rate, and gravity (MARG) sensor array is a key problem in mechatronic-related applications. This paper proposes a new method in which a quaternion-based Kalman filter scheme is designed. The quaternion kinematic equation is employed as the process model. With our previous contributions, we establish the measurement model of attitude quaternion from accelerometer and magnetometer, which is later proved to be the fastest (computationally) one among representative attitude determination algorithms of such sensor combination. Variance analysis is later given enabling the optimal updating of the proposed filter. The algorithm is implemented on real-world hardware where experiments are carried out to reveal the advantages of the proposed method with respect to conventional ones. The proposed approach is also validated on an unmanned aerial vehicle during a real flight. Results show that the proposed one is faster than any other Kalman-based ones and even faster than some complementary ones while the attitude estimation accuracy is maintained.