Nilsson, Martin (2006) Kalman Filtering with Unknown Noise Covariances. In: Reglermöte 2006, 30-31 May 2006, Stockholm, Sweden.
Official URL: http://www.drnil.com/
Since it is often difficult to identify the noise covariances for a Kalman filter, they are commonly considered design variables. If so, we can as well try to choose them so that the corresponding Kalman filter has some nice form. In this paper, we introduce a one-parameter subfamily of Kalman filters with the property that the covariance parameters cancel in the expression for the Kalman gain. We provide a simple criterion which guarantees that the implicitly defined process covariance matrix is positive definite.
|Item Type:||Conference or Workshop Item (Paper)|
|Uncontrolled Keywords:||discrete-time linear system, process noise, measurement noise, covariance, Kalman filter, discrete Riccati equation, singular value decomposition, Moore-Penrose pseudoinverse|
|Deposited By:||IAM Researcher|
|Deposited On:||18 Dec 2006|
|Last Modified:||18 Nov 2009 15:56|
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