Stochastic Integration Based Estimator: Robust Design and Stone Soup Implementation

This paper deals with state estimation of nonlinear stochastic dynamic models. In particular, the stochastic integration rule, which provides asymptotically unbiased estimates of the moments of nonlinearly transformed Gaussian random variables, is reviewed together with the recently introduced stoch...

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Vydané v:	2024 27th International Conference on Information Fusion (FUSION) s. 1 - 8
Hlavní autori:	Dunik, Jindrich, Matousek, Jakub, Straka, Ondrej, Blasch, Erik, Hiles, John, Niu, Ruixin
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	ISIF 08.07.2024
Predmet:	Filtering Filtering algorithms Heuristic algorithms Kalman filters MATLAB Nonlinear systems Prediction Prediction algorithms Random variables Smoothing Smoothing methods State estimation Stochastic integration rule Stochastic processes Stone Soup
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