The state-dependent Riccati equation-based estimator is becoming a popular estimation
tool for nonlinear systems since it does not use system linearization. In this paper, the state …

Ph. D. Thesis Title: Correlated Estimation Problems and the Ensemble Kalman Filter Author:
Jan Čurn Abstract: The Kalman filter is a recursive algorithm that estimates the state of a …

Parameter errors in dynamic and measurement models of dynamic systems can result in
poor state estimates when using a traditional Kalman filter structure. In dealing with these …

A novel covariance matching technique is proposed for estimating the states and unknown
entries of the process and measurement noise covariance matrices for additive white …

The two-stage Kalman estimator was originally proposed to reduce the computational
complexity of the augmented state Kalman filter. It was also applied to the tracking of …

ON JULY 2nd, 2016, the guidance, navigation, and control (GN&C) community lost its
eminent ambassador with the passing of Dr. Rudolf Emil Kalman. Although Dr. Kalman …

A nonlinear approximate Bayesian filter, named the minimum divergence filter, is developed
in which the state density is approximated by an assumed density. The parameters of the …

The authors provide the optimal solution of a two-stage estimation problem in the presence
of random bias. Under an algebraic constraint, the optimal estimate of the system state can …

This study discusses the development of a desensitised optimal filtering technique for
systems subject to plant and measurement model parameter uncertainties. Desensitised …

This paper presents a study of the reset step in the multiplicative extended Kalman filter
(MEKF). This filter is widely used for spacecraft attitude estimation, which typically involves …