This project presents the formulation and implementation of a Kalman filter based dynamic object tracking algorithm. Object tracking is one of the most fundamental problems in the area of visual ...

This library separates the system and measurement models, which are what truly define the state estimation problem, from the actual filter algorithms. Models are also defined as being linear or ...

The introduction of nonlinearity in the dynamic or measurement model corrupts the standard (linear) propagation of the mean and covariance. This chapter proposes methods for coping with such ...

Abstract: This paper proposes a Gaussian-Cauchy mixture maximum correntropy criterion Kalman filter algorithm (GCM_MCCKF) for robust state estimation in linear systems under non-Gaussian noise, ...