Robustness of a Kalman filter against uncertainties of noise covariances
Shuichi Sasa · 1998
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.