We introduce a mathematical formulation of feature-informed data assimilation (FIDA). In FIDA, the information about feature events, such as shock waves, level curves, wavefronts and peak value, in dynamical systems are used for the estimation of state variables and unknown parameters. The observation operator in FIDA is a set-valued functional, which is fundamentally different from the observation operators in conventional data assimilation. Demonstrated in three example, FIDA problems introduced in this note exist in a wide spectrum of applications in science and engineering.
@article{arxiv.2211.00256,
title = {Feature-Informed Data Assimilation -- Definitions and Illustrative Examples},
author = {Wei Kang and Daniel M. Tartakovsky and Apoorv Srivastava},
journal= {arXiv preprint arXiv:2211.00256},
year = {2022}
}