Document Type
Article
Publication Date
1-2002
Publication Title
IEEE Transactions on Aerospace and Electronic Systems,
Abstract
Kalman filters are commonly used to estimate the states of a dynamic system. However, in the application of Kalman filters there is often known model or signal information that is either ignored or dealt with heuristically. For instance, constraints on state values (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. A rigorous analytic method of incorporating state equality constraints in the Kalman filter is developed. The constraints may be time varying. At each time step the unconstrained Kalman filter solution is projected onto the state constraint surface. This significantly improves the prediction accuracy of the filter. The use of this algorithm is demonstrated on a simple nonlinear vehicle tracking problem
Repository Citation
Simon, Daniel J. and Chia, Tien Li, "Kalman Filtering with State Equality Constraints" (2002). Electrical and Computer Engineering Faculty Publications. 158.
https://engagedscholarship.csuohio.edu/enece_facpub/158
Original Citation
Simon, D. & Tien Li Chia. (2002). Kalman filtering with state equality constraints. Aerospace and Electronic Systems, IEEE Transactions on, 38(1), 128-136, doi: 10.1109/7.993234.
DOI
10.1109/7.993234
Version
Postprint
Publisher's Statement
© 2002 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Volume
38
Issue
1
