Parametric Kalman filter for chemical transport models

Parametric contour tracking using unscented Kalman filter

This paper presents an efficient method to integrate various spatial-temporal constraints to regularize the contour tracking. Specifically, the global shape prior, contour smoothness and object dynamics are addressed. First, the contour is represented as a parametric shape, based on which a causal smoothness constraint can be developed to exploit the local spatial constraint. The causality natu...

Rotated Unscented Kalman Filter for Two State Nonlinear Systems

In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yieldwith UKF for the most nonlinear systems. In this paper, we use a new approach for a two variablestate no...

Kalman filter sensitivity with respect to parametric noises uncertainty

The influence of the noises uncertainty on the Kalman filter performance is characterized by sensitivity functions. Relationships for computing these functions are derived and used both for synthesizing a Kalman filter with reduced sensitivity (KFRS) and a self-tuning Kalman filter (SKF). The results are illustrated by examples.

State Space Models and the Kalman Filter

The Particle Filter and Extended Kalman Filter methods for the structural system identification considering various uncertainties

Structural system identification using recursive methods has been a research direction of increasing interest in recent decades. The two prominent methods, including the Extended Kalman Filter (EKF) and the Particle Filter (PF), also known as the Sequential Monte Carlo (SMC), are advantageous in this field. In this study, the system identification of a shake table test of a 4-story steel struct...