Intelligent Systems and Control
In this paper the robustness of Kalman filtering against uncertainties in process and measurement noise covariances is discussed. It is shown that a standard Kalman filter may not be robust enough if the process and measurement noise covariances are changed. A new filter is proposed which addresses the uncertainties in process and measurement noise covariances and gives better results than the standard Kalman filter. This new filter is used in simulation to estimate the health parameters of an aircraft gas turbine engine.
Kosanam, Srikiran and Simon, Daniel J., "Kalman Filtering with Uncertain Noise Covariances" (2004). Electrical Engineering & Computer Science Faculty Publications. 196.
S. Kosanam and D. Simon. (2004). Kalman Filtering with Uncertain Noise Covariances, Intelligent Systems and Control, Honolulu, HI, 375-379.