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Journal of Sensors
Volume 2017, Article ID 9560108, 9 pages
Research Article

Linear Kalman Filter for Attitude Estimation from Angular Rate and a Single Vector Measurement

1College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China
2School of Automation, University of Electronic Science and Technology of China, Chengdu, China

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

Received 7 May 2017; Accepted 20 July 2017; Published 18 October 2017

Academic Editor: Mohannad Al-Durgham

Copyright © 2017 Shangqiu Shan 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.


In this paper, a new Kalman filtering scheme is designed in order to give the optimal attitude estimation with gyroscopic data and a single vector observation. The quaternion kinematic equation is adopted as the state model while the quaternion of the attitude determination from a strapdown sensor is treated as the measurement. Derivations of the attitude solution from a single vector observation along with its variance analysis are presented. The proposed filter is named as the Single Vector Observation Linear Kalman filter (SVO-LKF). Flexible design of the filter facilitates fast execution speed with respect to other filters with linearization. Simulations and experiments are conducted in the presence of large external acceleration and magnetic distortion. The results show that, compared with representative filtering methods and attitude observers, the SVO-LKF owns the best estimation accuracy and it consumes much less time in the fusion process.