Multilevel ensemble Kalman filtering

Hakon Hoel, Kody J. H. Law, Raul Tempone

Research output: Contribution to journalArticlepeer-review

67 Scopus citations

Abstract

This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.
Original languageEnglish (US)
Pages (from-to)1813-1839
Number of pages27
JournalSIAM Journal on Numerical Analysis
Volume54
Issue number3
DOIs
StatePublished - Jun 14 2016

Fingerprint

Dive into the research topics of 'Multilevel ensemble Kalman filtering'. Together they form a unique fingerprint.

Cite this