Sparse Reconstructions of Acoustic Source for Inverse Scattering Problems in Measure Space

TL;DR

This paper develops a mathematical framework for sparse acoustic source reconstruction in inverse scattering problems using Radon measure space, ensuring solution existence and stability, and employs a semismooth Newton method for numerical solutions.

Contribution

It introduces a novel sparse reconstruction approach in Radon measure space for inverse acoustic scattering, with a new weak solution concept and a numerical solution method.

Findings

Existence and uniqueness of solutions established.

Stable reconstruction guaranteed in Radon measure space.

Numerical examples demonstrate effectiveness of the method.

Abstract

This paper proposes a systematic mathematical analysis of both the direct and inverse acoustic scattering problem given the source in Radon measure space. For the direct problem, we investigate the well-posedness including the existence, the uniqueness, and the stability by introducing a special definition of the weak solution, i.e. \emph{very} weak solution. For the inverse problem, we choose the Radon measure space instead of the popular $L^1$ space to build the sparse reconstruction, which can guarantee the existence of the reconstructed solution. The sparse reconstruction problem can be solved by the semismooth Newton method in the dual space. Numerical examples are included.