Data-Driven Modeling for Wave-Propagation

Abstract

Many imaging modalities, such as ultrasound and radar, rely heavily on the ability to accurately model wave propagation. In most applications, the response of an object to an incident wave is recorded and the goal is to characterize the object in terms of its physical parameters (e.g., density or soundspeed). We can cast this as a joint parameter and state estimation problem. In particular, we consider the case where the inner problem of estimating the state is a weakly constrained data-assimilation problem. In this paper, we discuss a numerical method for solving this variational problem.