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.
Kalman Filtering with Uncertain Noise CovariancesIntelligent Systems and Control
Document TypeConference Proceeding
Citation InformationS. Kosanam and D. Simon. (2004). Kalman Filtering with Uncertain Noise Covariances, Intelligent Systems and Control, Honolulu, HI, 375-379.