Reduced Order Kalman Filtering without Model Reduction
Document Type
Article
Publication Date
2007
Publication Title
Control & Intelligent Systems
Abstract
This paper presents all optimal discrete time reduced order Kalman filter. The reduced order filter is used to estimate a linear combination of a subset of the state vector. Most previous approaches to reduced order filtering rely on a reduction of the model order. However, this paper takes the full model order into account. The reduced order filter is obtained by minimizing the trace of the estimation error covariance.
Repository Citation
Simon, Daniel J., "Reduced Order Kalman Filtering without Model Reduction" (2007). Electrical and Computer Engineering Faculty Publications. 147.
https://engagedscholarship.csuohio.edu/enece_facpub/147
Original Citation
Simon, D. D. (2007). Reduced Order Kalman Filtering without Model Reduction. Control & Intelligent Systems, 35(2), 169-174.
Volume
35
Issue
2
