In this paper the robustness of Kalman filtering against uncertainties in process and measurement noise covariances is discussed. It is shown that a standard Kalman filter may not be robust enough if the process and measurement noise covariances are changed. A new filter is proposed which addresses the uncertainties in process and measurement noise covariances and gives better results than the ...

This paper investigates the performance of the Kalman filter as a timing recovery system in tracking mode, subject to a wide range of operating conditions. Our simulation compares the Kalman filter and the phase-locked loop based on the number of divergences for various values of timing disturbance and SNR. They are shown to work equally well in low SNR and disturbance. However, the Kalman filt...

The practical aspects of efficient implementation of the Kalman Filter Bank for scenario analysis are considered. Such implementation have to shorten running time, computational cost, and memory demands, required for computer model of the Kalman Filter Bank. The first requirement is met by concurrent computing. The second and third requirements are satisfied by substitution the Equivalent Kalma...

An adaptive extended Kalman filter is developed and investigated for a transient heat transfer problem in which a high heat flux spot source is applied on one side of a thin plate and ultrasonic pulse time of flight is measured between spatially separated transducers on the opposite side of the plate. The novel approach is based on the uncertainty in the state model covariance and leverages tre...

The Kalman filter has been used successfully in different prediction applications or state determination of a system. One of the more important fields in computer vision is the object tracking. Different movement conditions and occlusions can hinder the vision tracking of an object. In this report we present the use of the Kalman filter as a predictor in vision tracking. We consider the capacit...

This paper describes the application of an unscented Kalman filter to a coal runof-mine bin. A dynamic model of the bin is derived using the principle of mass conservation. The dynamic model is nonlinear with unknown parameters that are identified using actual plant production data. The identified dynamic model is used by an unscented Kalman filter to update the states of the system to improve ...

There is a growing interest in using Kalman-filter models in brain modelling. In turn, it is of considerable importance to make Kalman-filters amenable for reinforcement learning. In the usual formulation of optimal control it is computed off-line by solving a backward recursion. In this technical note we show that slight modification of the linear-quadratic-Gaussian Kalman-filter model allows ...

In normal working conditions it is possible to achieve sufficient attitude estimation accuracy for a satellite using regular Kalman filter algorithm. On the other hand, when there is a fault in the measurements, the Kalman filter fails in providing the required accuracy and may even collapse over time. In this paper, a Robust Kalman filtering method is proposed for the attitude estimation probl...