Monotonicity-Based Regularization of Inverse Medium Scattering for Shape Reconstruction

Abstract. We consider the scattering of time-harmonic plane waves by a compactly supported inhomogeneous scattering obstacle governed by the Helmholtz equation. Given far field observations of the scattered fields corresponding to plane wave incident fields for all possible incident and observation directions, we study the inverse problem to recover the support of the scatterer. We propose a qualitative monotonicity-based regularization scheme which combines monotonicity-based shape reconstruction with one-step linearization to reconstruct a discrete approximation of the shape of the scatterer from noisy far field data. The purpose of the one-step linearization is to stabilize the monotonicity approach to shape reconstruction. We show that the monotonicity-based regularization scheme recovers the correct shape of the scatterer for noise-free data. Furthermore, we establish that the solution of the monotonicity-based regularization converges to the exact solution as the noise level tends to zero. We present numerical examples to illustrate our theoretical findings.

Authors

Institutions

Publication Details

Journal
SIAM Journal on Imaging Sciences
Published
2026-09-11
DOI
https://doi.org/10.1137/26m1854318
Primary Topic
Numerical methods in inverse problems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Monotonicity-Based Regularization of Inverse Medium Scattering for Shape Reconstruction

Jianli Xiang, Roland Griesmaier, Bastian Harrach
SIAM Journal on Imaging Sciences
Numerical methods in inverse problems
article

Monotonicity-Based Regularization of Inverse Medium Scattering for Shape Reconstruction

Jianli Xiang, Roland Griesmaier, Bastian Harrach
article en

Abstract

Abstract. We consider the scattering of time-harmonic plane waves by a compactly supported inhomogeneous scattering obstacle governed by the Helmholtz equation. Given far field observations of the scattered fields corresponding to plane wave incident fields for all possible incident and observation directions, we study the inverse problem to recover the support of the scatterer. We propose a qualitative monotonicity-based regularization scheme which combines monotonicity-based shape reconstruction with one-step linearization to reconstruct a discrete approximation of the shape of the scatterer from noisy far field data. The purpose of the one-step linearization is to stabilize the monotonicity approach to shape reconstruction. We show that the monotonicity-based regularization scheme recovers the correct shape of the scatterer for noise-free data. Furthermore, we establish that the solution of the monotonicity-based regularization converges to the exact solution as the noise level tends to zero. We present numerical examples to illustrate our theoretical findings.

SIAM Journal on Imaging SciencesVol. 19(3)
Karlsruhe Institute of Technology (DE), Goethe University Frankfurt (DE), China Three Gorges University (CN), Institut für Angewandte Statistik (DE)
Deutsche Forschungsgemeinschaft, National Natural Science Foundation of China, Central China Normal University
Sustainable cities and communities
Openalex Percentile: Top 76%
Numerical methods in inverse problems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.