Continuous-time and continuous-discrete-time unscented Rauch-Tung-Striebel smoothers

DOI10.1016/j.sigpro.2009.06.012zbMath1177.93085OpenAlexW2103777996MaRDI QIDQ1048801

Simo Särkkä

Publication date: 8 January 2010

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2009.06.012

zbMATH Keywords

unscented transformationcontinuous-time smootherunscented Kalman smootherunscented Rauch-Tung-Striebel smoother

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Applications of stochastic analysis (to PDEs, etc.) (60H30)

Related Items (3)

Expectation propagation for continuous time stochastic processes ⋮ The nonsequential fusion method for localization from unscented Kalman filter by multistation array buoys ⋮ Posterior inference on parameters of stochastic differential equations via non-linear Gaussian filtering and adaptive MCMC

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Stochastic models, estimation, and control. Vol. 2,3
• Parameter estimation and the CRLB with uncertain origin measurements
• Stochastic processes and filtering theory
• A survey of data smoothing for linear and nonlinear dynamic systems
• Sequential Monte Carlo Methods in Practice
• A new method for the nonlinear transformation of means and covariances in filters and estimators
• Optimal Estimation of Dynamic Systems
• Unscented Rauch--Tung--Striebel Smoother
• On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems
• On the Differential Equations Satisfied by Conditional Probablitity Densities of Markov Processes, with Applications
• Nonlinear Smoothing Theory
• Stochastic differential equations. An introduction with applications.

This page was built for publication: Continuous-time and continuous-discrete-time unscented Rauch-Tung-Striebel smoothers