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Linear Kalman Filter for Attitude Estimation from Angular Rate and a Single Vector Measurement
Joint Authors
Hou, Zhongxi
Wu, Jin
Shan, Shangqiu
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-18
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Shan, Shangqiu& Hou, Zhongxi& Wu, Jin. 2017. Linear Kalman Filter for Attitude Estimation from Angular Rate and a Single Vector Measurement. Journal of Sensors،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1187679
Modern Language Association (MLA)
Shan, Shangqiu…[et al.]. Linear Kalman Filter for Attitude Estimation from Angular Rate and a Single Vector Measurement. Journal of Sensors No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1187679
American Medical Association (AMA)
Shan, Shangqiu& Hou, Zhongxi& Wu, Jin. Linear Kalman Filter for Attitude Estimation from Angular Rate and a Single Vector Measurement. Journal of Sensors. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1187679
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1187679