Abstract
The paper deals with state estimation problem of nonlinear stochastic dynamic systems with a special focus on a software package supporting problem specification, system simulation, and state estimation itself. The developed package called Gaussian Filtering Toolbox is described, which is a practically oriented successor to the toolbox called Nonlinear Estimation Framework that was oriented rather towards academia with its generality and richness. The developed toolbox is described in terms of its usage and particularly the aspects leading to a better practical applicability. The key features of the toolbox, which are computational complexity reduction and numerical stability enhancement, are illustrated using two numerical examples.
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