8 citations · 34 across the 19 of their papers we have counts for
7 papers · 1 filter
Stone Soup: ADS-B-based Multi-Target Tracking with Stochastic Integration Filter
John Hiles, Jakub Matousek, Erik Blasch +3
This paper focuses on the multi-target tracking using the Stone Soup framework. In particular, we aim at evaluation of two multi-target tracking scenarios based on the simulated cl…
Interpretable Augmented Physics-Based Model for Estimation and Tracking
Ondřej Straka, Jindřich Duník, Pau Closas +1
State-space estimation and tracking rely on accurate dynamical models to perform well. However, obtaining an vaccurate dynamical model for complex scenarios or adapting to changes…
Unobservable Systems: No Problem for Noise Identification
Oliver Kost, Jindrich Dunik, Ivo Puncochar +1
This paper deals with the noise identification of a linear time-varying stochastic dynamic system described by the state-space model. In particular, the stress is laid on the desig…
Tensor Train Discrete Grid-Based Filters: Breaking the Curse of Dimensionality
J. Matoušek, M. Brandner, J. Duník +1
This paper deals with the state estimation of stochastic systems and examines the possible employment of tensor decompositions in grid-based filtering routines, in particular, the…
Efficient Spectral Differentiation in Grid-Based Continuous State Estimation
Jakub Matousek, Jindrich Dunik, Marek Brandner
This paper deals with the state estimation of stochastic models with continuous dynamics. The aim is to incorporate spectral differentiation methods into the solution to the Fokker…
Stochastic Integration Based Estimator: Robust Design and Stone Soup Implementation
Jindrich Dunik, Jakub Matousek, Ondrej Straka +3
This paper deals with state estimation of nonlinear stochastic dynamic models. In particular, the stochastic integration rule, which provides asymptotically unbiased estimates of t…
Data-Augmented Numerical Integration in State Prediction: Rule Selection
Jindrich Dunik, Ladislav Kral, Jakub Matousek +2
This paper deals with the state prediction of nonlinear stochastic dynamic systems. The emphasis is laid on a solution to the integral Chapman-Kolmogorov equation by a deterministi…