Research Summaries

Back Computational Methods and Nonlinear Filters for Data Assimilation

Fiscal Year 2018
Division Graduate School of Engineering & Applied Science
Department Applied Mathematics
Investigator(s) Kang, Wei
Sponsor Naval Research Laboratory (Navy)
Summary The proposed research of the one-year project aims at a comprehensive approach that deals with the multiple limitations in Kalman filters. The goal is to invent a design framework so that algorithms can be optimized for various problem sizes and computational platforms. For the approach, we plan to explore ideas that take the advantage of sparse covariance matrices and enable unscented Kalman Filters (UKFs) for large scale systems.
Keywords Computational Algorithm Data Assimilation Kalman Filter
Publications Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal