Through-the-Wall Nonlinear SAR Imaging

TL;DR

This paper presents a fully nonlinear SAR imaging method for through-the-wall scenarios using a convexification inversion scheme, achieving higher accuracy than traditional linearized models in both simulated and real data.

Contribution

It introduces a globally convergent nonlinear inversion approach for through-the-wall SAR imaging that overcomes local minima issues inherent in linearized models.

Findings

The proposed method accurately estimates target dielectric properties behind walls.

Numerical results outperform traditional Born approximation-based methods.

The approach is validated on both simulated and experimental data.

Abstract

An inverse scattering problem for SAR data in application to through-the-wall imaging is addressed. In contrast with the conventional algorithms of SAR imaging, that work with the linearized mathematical model based on the Born approximation, the fully nonlinear case is considered here. To avoid the local minima problem, the so-called "convexification" globally convergent inversion scheme is applied to approximate the distribution of the slant range (SR) dielectric constant in the 3-D domain. The benchmark scene of this paper comprises a homogeneous dielectric wall and different dielectric targets hidden behind it. The results comprise two dimensional images of the SR dielectric constant of the scene of interest. Numerical results are obtained by the proposed inversion method for both the computationally simulated and experimental data. Our results show that the values, cross-range sizes and locations of SR dielectric constants for targets hidden behind the wall are close to those of real targets. Numerical comparison with the solution of the linearized inverse scattering problem provided by the Born approximation, commonly used in conventional SAR imaging, shows a significantly better accuracy of our results.