The Kalman filter requires knowledge about the noise statistics. In practical applications, however, the noise covariances are generally not known. A method for estimating noise covariances from process data has been investigated. The method gives a least-squares estimate of the noise covariances, which can be used to compute the Kalman filter gain.
Computer-aided Chemical Engineering, 2007, p. 859-864
Covariance Estimation; State estimation; Kalman filter
Main Research Area:
Computer - Aided Chemical Engineering
17th European Symposium on Computer Aided Process Engineering, 2007