A simple procedure to include state inequality constraints in the unscented Kalman filter is
proposed. With this procedure, the information of active state constraints influences the state …

The Kalman filter is the minimum-variance state estimator for linear dynamic systems with
Gaussian noise. Even if the noise is non-Gaussian, the Kalman filter is the best linear …

We discuss two separate techniques for Kalman filtering in the presence of state space
equality constraints. We discuss these methods and then prove that despite the lack of …

This article is concerned with the state estimation problem for linear systems with linear state
equality constraints. We re-examine constrained Kalman filter variations and propose an …

Kalman filters are commonly used to estimate the states of a dynamic system. However, in
the application of Kalman filters there is often known model or signal information that is …

An analytic method was developed by D. Simon and TL Chia to incorporate linear state
equality constraints into the Kalman filter. When the state constraint was nonlinear …

This paper considers the state-estimation problem with a constraint on the data-injection
gain. Special cases of this problem include the enforcing of a linear equality constraint in the …

The extended Kalman filter (EKF) has been an important tool for state estimation of
nonlinear systems since its introduction. However, the EKF does not possess the same …

Constraints on state variables are commonly encountered in dynamic state estimation in the
form of algebraic equality and/or inequality constraints. For weakly nonlinear systems, the …

A priori state vector and error covariance computation for the Unscented Kalman Filter (UKF)
is described. The original UKF propagates multiple sigma points to compute the a priori …