Kalman filtering with state constraints: a survey of linear and nonlinear algorithms
D Simon - IET Control Theory & Applications, 2010 - IET
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 …
Gaussian noise. Even if the noise is non-Gaussian, the Kalman filter is the best linear …
Robust adaptive Kalman filtering with unknown inputs
A Moghaddamjoo, RL Kirlin - IEEE Transactions on Acoustics …, 1989 - ieeexplore.ieee.org
A method is proposed to adapt the Kalman filter to the changes in the input forcing functions
and the noise statistics. The resulting procedure is stable in the sense that the duration of …
and the noise statistics. The resulting procedure is stable in the sense that the duration of …
Robust Kalman filtering for nonlinear multivariable stochastic systems in the presence of non‐Gaussian noise
V Stojanovic, N Nedic - International Journal of Robust and …, 2016 - Wiley Online Library
The presence of outliers can considerably degrade the performance of linear recursive
algorithms based on the assumptions that measurements have a Gaussian distribution …
algorithms based on the assumptions that measurements have a Gaussian distribution …
A simple method for the control of divergence in Kalman-filter algorithms
H Sriyananda - International Journal of Control, 1972 - Taylor & Francis
It is found that, under certain conditions, the estimation errors produced by the Standard
Kalman-filter algorithm increase rapidly, and become unbounded, even though the …
Kalman-filter algorithm increase rapidly, and become unbounded, even though the …
Kalman filtering of systems with parameter uncertainties—a survey
CT Leondes, JO PEARSON - International Journal of Control, 1973 - Taylor & Francis
A survey of analysis and synthesis techniques for Kalman-Bucy filtering of systems with
parameter uncertainties in the plant matrix and. noise covariance matrices is given …
parameter uncertainties in the plant matrix and. noise covariance matrices is given …
Robust adaptive Kalman filtering
AR Moghaddamjoo, RL Kirlin - Approximate Kalman Filtering, 1993 - World Scientific
In this chapter we first survey several adaptive procedures under the assumption that the
noise is Gaussian. Then several different approaches for adaptation to the unknown …
noise is Gaussian. Then several different approaches for adaptation to the unknown …
Kalman filtering with intermittent observations: Bounds on the error covariance distribution
When measurements are subject to random losses, the covariance of the estimation error of
a state estimator becomes a random variable. In this paper we present bounds on the …
a state estimator becomes a random variable. In this paper we present bounds on the …
Lower order optimal linear filtering of nonstationary random sequences
K Brammer - IEEE Transactions on Automatic Control, 1968 - ieeexplore.ieee.org
The following deals with the discrete-time linear minimum-variance filtering of nonstationary
random processes. The dynamics of the signal and colored noise processes are …
random processes. The dynamics of the signal and colored noise processes are …
Robust two-stage Kalman filters for systems with unknown inputs
CS Hsieh - IEEE Transactions on Automatic Control, 2000 - ieeexplore.ieee.org
A method is developed for the state estimation of linear time-varying discrete systems with
unknown inputs. By making use of the two-stage Kalman filtering technique and a proposed …
unknown inputs. By making use of the two-stage Kalman filtering technique and a proposed …