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 alternative derivation of the optimal constrained Kalman filter for time variant systems. This results in an oblique state projection that gives the smallest error covariance. A simple example illustrates the performance of the different Kalman filters
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the a...
International audienceThis paper presents a comparison in terms of accuracy and complexity between t...
In this paper, we consider a dynamic linear system in statespace form where the observation equation...
This paper deals with state estimation problem for linear systems with state equality constraints. U...
For linear dynamic systems with white process and measurement noise, the Kalman filter is known to b...
We discuss two separate techniques for Kalman Filtering in the presence of state space equality cons...
The Kalman filter is the minimum-variance state estimator for linear dynamic systems with Gaussian n...
Kalman filters are commonly used to estimate the states of a dynamic system. However, in the applica...
Both constrained and unconstrained optimization problems regularly appear in recursive tracking prob...
The state space description of some physical systems possess nonlinear equality constraints between ...
Abstract – In [Simon and Chia, 2002], an analytic method was developed to incorporate linear state e...
International audienceThis paper presents a method for dealing with Kalman filtering under particula...
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the a...
Kalman fllters are often used to estimate the state variables of a dynamic system. However, in the a...
The Kalman filter computes the maximum a posteriori (MAP) estimate of the states for linear state sp...
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the a...
International audienceThis paper presents a comparison in terms of accuracy and complexity between t...
In this paper, we consider a dynamic linear system in statespace form where the observation equation...
This paper deals with state estimation problem for linear systems with state equality constraints. U...
For linear dynamic systems with white process and measurement noise, the Kalman filter is known to b...
We discuss two separate techniques for Kalman Filtering in the presence of state space equality cons...
The Kalman filter is the minimum-variance state estimator for linear dynamic systems with Gaussian n...
Kalman filters are commonly used to estimate the states of a dynamic system. However, in the applica...
Both constrained and unconstrained optimization problems regularly appear in recursive tracking prob...
The state space description of some physical systems possess nonlinear equality constraints between ...
Abstract – In [Simon and Chia, 2002], an analytic method was developed to incorporate linear state e...
International audienceThis paper presents a method for dealing with Kalman filtering under particula...
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the a...
Kalman fllters are often used to estimate the state variables of a dynamic system. However, in the a...
The Kalman filter computes the maximum a posteriori (MAP) estimate of the states for linear state sp...
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the a...
International audienceThis paper presents a comparison in terms of accuracy and complexity between t...
In this paper, we consider a dynamic linear system in statespace form where the observation equation...