Revealing the Invisible: Imaging Through Non-Radiating Subspace

Abstract

This paper presents a novel modification to the subspace optimization method (SOM) for solving inverse scattering problems in diverse background media. By incorporating sequential quadratic programming (SQP), a fast and accurate optimization technique, our approach aims to improve the reconstruction of dielectric objects buried in complex environments. We investigate the influence of non-radiating (NR) subspace reconstruction on imaging quality by analyzing the induced current-exterior field mapping operator's singular values. The scattering formulation of direct problems is performed through numerical methods such as coupled dipole method, finite elements-boundary integral, and electric field integral equations. Radiating and non-radiating objective functions are defined and minimized using SQP to evaluate the effectiveness of the proposed method. Numerical experiments demonstrate significant enhancements in imaging quality, robustness, and computational efficiency compared to existing techniques. This modified SOM offers a promising avenue for precise and reliable reconstruction of electromagnetic scattering objects, with potential applications in various fields including medical imaging, remote sensing, and non-destructive evaluation.