Inverse Obstacle Scattering from Multi-Frequency Near-Field Backscattering Data

Fuente: arXiv
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Auteurs principaux: Li, Jialei, Liu, Xiaodong
Format: Preprint
Publié: 2026
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author Li, Jialei
Liu, Xiaodong
author_facet Li, Jialei
Liu, Xiaodong
contents This paper addresses the inverse obstacle scattering problem of simultaneously reconstructing the obstacle geometry and boundary conditions from multi-frequency near-field backscattering data. We first establish rigorous high-frequency asymptotic expansions for the scattered near-field, leveraging pseudo-differential operators (PDOs) to characterize the interaction between wavefront propagation and obstacle boundaries, where the principal symbol of the PDO governs the leading-order behavior of the scattering field. Based on these asymptotic results, we prove a global uniqueness theorem for the simultaneous recovery of the obstacle shape and impedance boundary condition under convexity assumptions. Furthermore, we develop a three-stage numerical reconstruction framework: (1) qualitative shape reconstruction via the direct sampling method; (2) quantitative boundary refinement via shape optimization; and (3) decoupled reconstruction of the boundary condition. A highlight of this algorithm is that all the three steps avoid computing the direct problem. Numerical experiments are presented to verify the robustness and efficiency of the proposed algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2604_09642
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Inverse Obstacle Scattering from Multi-Frequency Near-Field Backscattering Data
Li, Jialei
Liu, Xiaodong
Analysis of PDEs
Numerical Analysis
35P25, 45Q05, 78A46
This paper addresses the inverse obstacle scattering problem of simultaneously reconstructing the obstacle geometry and boundary conditions from multi-frequency near-field backscattering data. We first establish rigorous high-frequency asymptotic expansions for the scattered near-field, leveraging pseudo-differential operators (PDOs) to characterize the interaction between wavefront propagation and obstacle boundaries, where the principal symbol of the PDO governs the leading-order behavior of the scattering field. Based on these asymptotic results, we prove a global uniqueness theorem for the simultaneous recovery of the obstacle shape and impedance boundary condition under convexity assumptions. Furthermore, we develop a three-stage numerical reconstruction framework: (1) qualitative shape reconstruction via the direct sampling method; (2) quantitative boundary refinement via shape optimization; and (3) decoupled reconstruction of the boundary condition. A highlight of this algorithm is that all the three steps avoid computing the direct problem. Numerical experiments are presented to verify the robustness and efficiency of the proposed algorithm.
title Inverse Obstacle Scattering from Multi-Frequency Near-Field Backscattering Data
topic Analysis of PDEs
Numerical Analysis
35P25, 45Q05, 78A46
url https://arxiv.org/abs/2604.09642