Title :
Robustness of a Kalman filter against uncertainties of noise covariances
Author_Institution :
Nat. Aerosp. Lab., Sci. & Technol. Agency, Tokyo, Japan
Abstract :
The robustness of a Kalman filter against uncertainties of noise covariances is discussed. When covariance matrices of process noise and observation noise change from their nominal levels multiplied by random variables, a Kalman filter designed for the nominal noise condition is shown to be more robust than an observer designed by the pole placement technique in terms of the amount of deviation of the estimation accuracy from a nominal value
Keywords :
Kalman filters; covariance matrices; filtering theory; noise; observers; uncertain systems; Kalman filter robustness; covariance matrices; noise covariance uncertainty; observation noise; pole placement; process noise; random variables; Covariance matrix; Estimation error; Filters; Gaussian noise; Noise level; Noise robustness; Riccati equations; State estimation; Steady-state; Uncertainty;
Conference_Titel :
American Control Conference, 1998. Proceedings of the 1998
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-4530-4
DOI :
10.1109/ACC.1998.703050
