Multilevel ensemble Kalman filtering
Numerical Analysis
2016-06-30 v2 Probability
Computation
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.
Keywords
Cite
@article{arxiv.1502.06069,
title = {Multilevel ensemble Kalman filtering},
author = {Håkon Hoel and Kody J. H. Law and Raul Tempone},
journal= {arXiv preprint arXiv:1502.06069},
year = {2016}
}