Imaging of locally rough surfaces from intensity-only far-field or near-field data

TL;DR

This paper introduces a recursive Newton iteration algorithm for reconstructing locally rough surfaces from intensity-only data, utilizing multi-frequency incident fields and a fast solver, demonstrating stability and accuracy in numerical tests.

Contribution

It develops a novel multi-frequency approach with superposed plane waves for phaseless data, enabling simultaneous shape and location reconstruction of local surface perturbations.

Findings

Algorithm accurately reconstructs local surface features.

Method is stable with multiple-scale profiles.

Reconstruction is effective with intensity-only data.

Abstract

This paper is concerned with a nonlinear imaging problem, which aims to reconstruct a locally perturbed, perfectly reflecting, infinite plane from intensity-only (or phaseless) far-field or near-field data. A recursive Newton iteration algorithm in frequencies is developed to reconstruct the locally rough surface from multi-frequency intensity-only far-field or near-field data, where the fast integral equation solver developed in [39] is used to solve the direct scattering problem in each iteration. For the case with far-field data, a main feature of our work is that the incident field is taken as a superposition of two plane waves with different directions rather than one plane wave, so the location and shape of the local perturbation of the infinite plane can be reconstructed simultaneously from intensity-only far-field data with multiple wave numbers. This is different from previous work on inverse scattering from phaseless far-field data, where only the shape reconstruction was considered due to the translation invariance property of the phaseless far-field pattern corresponding to one plane wave as the incident field. Finally, numerical examples are carried out to demonstrate that our reconstruction algorithm is stable and accurate even for the case of multiple-scale profiles.