Reduced-rank unscented Kalman filtering using Cholesky-based decomposition

DOI10.1080/00207170801891724zbMath1148.93349OpenAlexW2048758050MaRDI QIDQ3536500

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Publication date: 21 November 2008

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207170801891724

zbMATH Keywords

data assimilationnonlinear state estimationreduced-rank Kalman filter

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Decentralized systems (93A14) Large-scale systems (93A15)

Related Items (3)

A reduced basis Kalman filter for parametrized partial differential equations ⋮ A local sigma-point unscented Kalman filter for geophysical data assimilation ⋮ Integrated methodology for state and parameter estimation of spark-ignition engines

Uses Software

• EnKF

Cites Work

• Tidal flow forecasting using reduced rank square root filters
• Square-root algorithms for least-squares estimation
• A new method for the nonlinear transformation of means and covariances in filters and estimators
• Dynamic Data Assimilation

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