A Fast Inverse Scattering Imaging Method by Applying Virtual Experiments to T-Matrix Scheme

Yongji Gan,Chengyou Yin,Qimeng Fan,Anqi Li

doi:10.1109/access.2020.3034018

Yongji Gan, Chengyou Yin + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.3034018

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Abstract

As a non-iterative linear inverse scattering imaging method, the linear sampling method (LSM) has the merits of easy implementation and high computational efficiency. In this article, based on the LSM and T-matrix method, we propose a fast method to reconstruct the target medium parameters. First, we use the LSM qualitative imaging method to estimate the contour of the target. Then, the preprocessing information of the LSM is applied to the virtual experiment circles in the framework of T-matrix method. In this way, we avoid the inversion of the matrix and only need to solve a series of univariate equations. Numerical simulation results show that the reconstruction accuracy of the proposed method is similar to that of LSM quantitative imaging method, but it has higher calculation accuracy and wider application range. Although the calculation accuracy is not as good as the contrast source inversion (CSI) method, the proposed method has huge advantages in terms of calculation efficiency.

Highlights

Electromagnetic inverse scattering is dedicated to reconstructing the characteristics of the object from the measured scattered field data
We use simulation data to verify the effectiveness of the proposed method, and compare it with the linear sampling method (LSM) quantitative imaging method and the contrast source inversion (CSI) method
Compared with the LSM quantitative imaging method, the proposed method has higher computational efficiency. It can be seen from the table that the calculation time of the proposed method is an order of magnitude faster than that of the CSI method

Summary

INTRODUCTION

Electromagnetic inverse scattering is dedicated to reconstructing the characteristics of the object from the measured scattered field data. Nonlinear methods include modified gradient method (MGM) [11], contrast source inversion (CSI) method [12, 13], subspace optimization method (SOM) [14], and so on Unlike linear methods, these methods use iteration to optimize reconstruction results. If we traverse all the sampling points inside the contour, we can get the media parameters in the entire target contour In this way, we avoid matrix inversion, which further reduces the computational burden. Throughout this article, the time factor e j t is adopted

IMAGING FRAMEWORK BASED ON T-MATRIX METHOD

LINEAR SAMPLING METHOD FOR QUALITATIVE IMAGING

SIMULATION CONDITIONS

EXAMPLES Example 1

CONCLUSION