3 citations · 17 across the 15 of their papers we have counts for
16 papers
Dual Approach to Inverse Covariance Intersection Fusion
Jiří Ajgl, Ondřej Straka
Linear fusion of estimates under the condition of no knowledge of correlation of estimation errors has reached maturity. On the other hand, various cases of partial knowledge are s…
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…
Aspects of density approximation by tensor trains
Jiří Ajgl, Ondřej Straka
Point-mass filters solve Bayesian recursive relations by approximating probability density functions of a system state over grids of discrete points. The approach suffers from the…
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…
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…