Random walks in frequency and the reconstruction of obstacles with cavities from multi-frequency data

TL;DR

This paper introduces a novel random walk frequency continuation method for reconstructing obstacles with cavities from multi-frequency scattering data, improving robustness over traditional methods but still facing challenges in extreme cases.

Contribution

It proposes a modified continuation-in-frequency approach that follows a random walk in frequency, enhancing cavity reconstruction robustness in inverse obstacle scattering.

Findings

Random walk frequency method shows increased robustness in cavity recovery.

Reconstruction results are consistent for non-cavity boundary parts.

Method can still fail in extreme cavity cases.

Abstract

Inverse obstacle scattering is the recovery of an obstacle boundary from the scattering data produced by incident waves. This shape recovery can be done by iteratively solving a PDE-constrained optimization problem for the obstacle boundary. While it is well known that this problem is typically non-convex and ill-posed, previous investigations have shown that in many settings these issues can be alleviated by using a continuation-in-frequency method and introducing a regularization that limits the frequency content of the obstacle boundary. It has been recently observed that these techniques can fail for obstacles with pronounced cavities, even in the case of penetrable obstacles where similar optimization and regularization methods work for the equivalent problem of recovering a piecewise constant wave speed. The present work investigates the recovery of obstacle boundaries for impenetrable, sound-soft media with pronounced cavities, given multi-frequency scattering data. Numerical examples demonstrate that the problem is sensitive to the choice of iterative solver used at each frequency and the initial guess at the lowest frequency. We propose a modified continuation-in-frequency method which follows a random walk in frequency, as opposed to the standard monotonically increasing path. This method shows some increased robustness in recovering cavities, but can also fail for more extreme examples. An interesting phenomenon is observed that while the obstacle reconstructions obtained over several random trials can vary significantly near the cavity, the results are consistent for non-cavity parts of the boundary.