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 …

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 …

Kalman filtering in the presence of white process and measurement noises having unknown
means and covariances is considered. Only stationary linear discrete stochastic systems are …

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 …

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 Q, the measurement noise covariance …

The behavior of the continuous-time Kalman filter under incorrect noise covariances is
analyzed. The filter performance is quantified by the actual state error covariance. Through …

Noise distribution arising in certain applications frequently deviates from the assumed
gaussian model, often being characterized by heavier tails generating the outliers. Since, in …

The Kalman filter is frequently used for state estimation in state-space models when the
standard Gaussian noise assumption does not apply. A problem arises, however, in that …

In this paper, an extension of the standard Kalman filtering for the dynamical systems with
white noises to finite-time correlated noises is addressed. Although one can augment the …