Optimal Attitude Determination from Vector Sensors Using Fast Analytical Singular Value Decomposition
Joint Authors
Gong, Xiangyang
Wu, Jin
Liu, Zhuohua
Liu, Wei
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-06-27
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
A novel algorithm is proposed in this paper to solve the optimal attitude determination formulation from vector observation pairs, that is, the Wahba problem.
We propose here a fast analytic singular value decomposition (SVD) approach to obtain the optimal attitude matrix.
The derivations and mandatory proofs are presented to clarify the theory and support its feasibility.
Through simulation experiments, the proposed algorithm is validated.
The results show that it maintains the same attitude determination accuracy and robustness with conventional methodologies but significantly reduces the computation time.
American Psychological Association (APA)
Liu, Zhuohua& Liu, Wei& Gong, Xiangyang& Wu, Jin. 2018. Optimal Attitude Determination from Vector Sensors Using Fast Analytical Singular Value Decomposition. Journal of Sensors،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1201811
Modern Language Association (MLA)
Liu, Zhuohua…[et al.]. Optimal Attitude Determination from Vector Sensors Using Fast Analytical Singular Value Decomposition. Journal of Sensors No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1201811
American Medical Association (AMA)
Liu, Zhuohua& Liu, Wei& Gong, Xiangyang& Wu, Jin. Optimal Attitude Determination from Vector Sensors Using Fast Analytical Singular Value Decomposition. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1201811
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201811