Document Type
Article
Publication Date
2-1-2006
Publication Title
IEEE Transactions on Signal Processing
Abstract
This paper presents a game theory approach to the constrained state estimation of linear discrete time dynamic systems. In the application of state estimators, there is often known model or signal information that is either ignored or dealt with heuristically. For example, constraints on the state values (which may be based on physical considerations) are often neglected because they do not easily fit into the structure of the state estimator. This paper develops a method for incorporating state equality constraints into a minimax state estimator. The algorithm is demonstrated on a simple vehicle tracking simulation.
Repository Citation
Simon, Daniel J., "A Game Theory Approach to Constrained Minimax State Estimation" (2006). Electrical and Computer Engineering Faculty Publications. 8.
https://engagedscholarship.csuohio.edu/enece_facpub/8
Original Citation
Simon, D. (2006). A game theory approach to constrained minimax state estimation. Ieee Transactions on Signal Processing, 54, 2, 405-412.
DOI
10.1109/TSP.2005.861732
Version
Postprint
Publisher's Statement
(c) 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.
Volume
54
Issue
2
Included in
Electrical and Computer Engineering Commons, Systems Engineering and Multidisciplinary Design Optimization Commons
