Estimation of steady-state Kalman filter gain Page 1 944 IEEE TRANSACTIONS ON
AUTOMATIC CONIXOL, VOL. AC-23, KO. 5, OCTOBER 1978 h5 t I\ / -1.5 ', /' -2.5 8L-n I I I I I …

A direct approach to identify the noise covariances of Kalman filtering Page 1 Page 2 842
IBEE TRANSACTIONS ON AuTohIAnC CONTROL, VOL. AC-25, NO. 4, AUGUST 1980 The …

This paper gives an optimal solution of the two-stage Kalman filter for linear stochastic
systems subject to random bias. It is shown that the state estimate can be expressed as xkk …

Analysis tools are developed that can be effectively used to study the performance
degradation of a filter when incorrect models of the state and measurement noise …

The optimum filtering results of Kalman filtering for linear dynamic systems require an exact
knowledge of the process noise covariance matrix Qk, the measurement noise covariance …

The optimum filtering results of Kalman filtering for linear dynamic systems require an exact
knowledge of the process noise covariance matrix Q, the measurement noise covariance …

A suboptimal dynamic compensator to be used in conjunction with the ordinary discrete-time
Kalman filter is derived. The resultant compensated Kalman filter has the property that …

A Kalman filter requires an exact knowledge of the process noise covariance matrix Q and
the measurement noise covariance matrix R. Here we consider the case in which the true …

The effect of modeling errors in a linear discrete stochastic system upon the Kalman filter
state estimates is investigated. Errors in both plant dynamics and noise covariances are …

This note introduces an extended environment for Kalman filtering that considers also the
presence of additive noise on input observations in order to solve the problem of optimal …