MULTILEVEL ENSEMBLE TRANSFORM PARTICLE FILTERING
- This paper extends the multilevel Monte Carlo variance reduction technique to nonlinear filtering. In particular, multilevel Monte Carlo is applied to a certain variant of the particle filter, the ensemble transform particle filter (EPTF). A key aspect is the use of optimal transport methods to re-establish correlation between coarse and fine ensembles after resampling; this controls the variance of the estimator. Numerical examples present a proof of concept of the effectiveness of the proposed method, demonstrating significant computational cost reductions (relative to the single-level ETPF counterpart) in the propagation of ensembles.
| Author details: | A. Gregory, C. J. Cotter, Sebastian ReichORCiDGND |
|---|---|
| DOI: | https://doi.org/10.1137/15M1038232 |
| ISSN: | 1064-8275 |
| ISSN: | 1095-7197 |
| Title of parent work (English): | SIAM journal on scientific computing |
| Publisher: | Society for Industrial and Applied Mathematics |
| Place of publishing: | Philadelphia |
| Publication type: | Article |
| Language: | English |
| Year of first publication: | 2016 |
| Publication year: | 2016 |
| Release date: | 2020/03/22 |
| Tag: | multilevel Monte Carlo; optimal transport; sequential data assimilation |
| Volume: | 38 |
| Number of pages: | 22 |
| First page: | A1317 |
| Last Page: | A1338 |
| Funding institution: | Science and Solutions to a Changing Planet DTP; Natural Environmental Research Council |
| Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik |
| Peer review: | Referiert |
