Three dimensional through-wall imaging: Inverse scattering problems with an inhomogeneous background medium

2015 ◽  
Author(s):  
Rui Chen ◽  
Zhun Wei ◽  
Xudong Chen
Keyword(s):  
Inverse Scattering ◽  
Three Dimensional ◽  
Scattering Problems ◽  
Background Medium ◽  
Inverse Scattering Problems ◽  
Wall Imaging

scholarly journals Contraction Integral Equation for Three-Dimensional Electromagnetic Inverse Scattering Problems

2019 ◽  
Vol 5 (2) ◽  
pp. 27 ◽  
Author(s):  
Yu Zhong ◽  
Kuiwen Xu
Keyword(s):  
Integral Equation ◽  
Inverse Scattering ◽  
Contraction Mapping ◽  
Three Dimensional ◽  
Nonlinear Problems ◽  
Optimization Method ◽  
Scattering Problems ◽  
Physical Reason ◽  
Inverse Scattering Problems ◽  
Highly Nonlinear

Inverse scattering problems (ISPs) stand at the center of many important imaging applications, such as geophysical explorations, industrial non-destructive testing, bio-medical imaging, etc. Recently, a new type of contraction integral equation for inversion (CIE-I) has been proposed to tackle the two-dimensional electromagnetic ISPs, in which the usually employed Lippmann–Schwinger integral equation (LSIE) is transformed into a new form with a modified medium contrast via a contraction mapping. With the CIE-I, the multiple scattering effects, i.e., the physical reason for the nonlinearity in the ISPs, is substantially suppressed in estimating the modified contrast, without compromising physical modeling. In this paper, we firstly propose to implement this new CIE-I for the three-dimensional ISPs. With the help of the FFT type twofold subspace-based optimization method (TSOM), when handling the highly nonlinear problems with strong scatterers, those with higher contrast and/or larger dimensions (in terms of wavelengths), the performance of the inversions with CIE-I is much better than the ones with the LSIE, wherein inversions usually converge to local minima that may be far away from the solution. In addition, when handling the moderate scatterers (those the LSIE modeling can still handle), the convergence speed of the proposed method with CIE-I is much faster than the one with the LSIE. Secondly, we propose to relax the contraction mapping condition, i.e., different contraction mappings are used in updating contrast sources and contrast, and we find that the convergence can be further accelerated. Several numerical tests illustrate the aforementioned interests.

scholarly journals An Efficient Technique for Solving Inhomogeneous Electromagnetic Inverse Scattering Problems

2020 ◽  
Vol 20 (1) ◽  
pp. 64-72 ◽  
Author(s):  
Mohamed Elkattan
Keyword(s):  
Inverse Scattering ◽  
Scattering Problem ◽  
Three Dimensional ◽  
Inverse Scattering Problem ◽  
Scattered Data ◽  
Global Minimization ◽  
Scattering Problems ◽  
Inverse Scattering Problems ◽  
Cooling Schedules ◽  
Electromagnetic Inverse Scattering

The electromagnetic inverse scattering approach seeks to obtain the electric characteristics of a scatterer using information about the source and the scattered data. The inverse scattering problem usually suffers from limited knowledge about the scatterer used, which makes its solution more challenging than the forward problem. This paper presents an inversion approach to estimating the unknown electric properties of a two- and three-dimensional inhomogeneous scatterer. The presented approach considers the inverse scattering problem as a global minimization problem with a meshless forward formulation for the computation of the scattered electromagnetic field. Various simulated annealing cooling schedules are applied and assessed to solve the problem, and the results of several case studies are presented for both two- and three-dimensional electromagnetic inverse scattering problems.

Multi-resolution subspace-based optimization method for solving three-dimensional inverse scattering problems

2015 ◽  
Vol 32 (11) ◽  
pp. 2218 ◽  
Author(s):  
Xiuzhu Ye ◽  
Lorenzo Poli ◽  
Giacomo Oliveri ◽  
Yu Zhong ◽  
Krishna Agarwal ◽  
...  
Keyword(s):  
Inverse Scattering ◽  
Three Dimensional ◽  
Optimization Method ◽  
Scattering Problems ◽  
Inverse Scattering Problems
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