Research Summaries

Back Observability in Data Assimilation and Optimal Sensor Configuration

Fiscal Year 2012
Division Graduate School of Engineering & Applied Science
Department Applied Mathematics
Investigator(s) Kang, Wei
Sponsor Naval Research Laboratory (Navy)
Summary The objective of this project is to develop and validate mathematical concepts and numerical algorithms for the evaluation and optimal design of sensor configuration in data assimilations. In the previous work, the concept of observability was defined for the problem of data assimilation; the concept was numerically verified based on a model of the Burgers equation using Monte Carlo simulations and traditional data assimilation methods; as a set of optimal fixed sensor locations were found for the Burgers equation. For future research, the objectives include exploring the observability and optimal motion planning for moving sensors; investigating the robustness of optimal sensor locations; developing computational algorithms that are scalable to large size problems; and, for the long term, developing computational algorithms for maximizing the observability of forecast models.
Keywords Observability, Data Assimilation
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