Application of Support Vector Machines for Estimating Wall Parameters in Through-Wall Radar Imaging

Hua-Mei Zhang,Fang-Fang Wang,Jun-Lin An,Ye-Rong Zhang

doi:10.1155/2015/456123

Abstract

In through-wall radar imaging (TWRI), ambiguities in wall characteristics including the thickness and the relative permittivity will distort the image and shift the imaged target position. To quickly and accurately estimate the wall parameters, an approach based on a support vector machine (SVM) is proposed. In TWRI problem, the nonlinearity is embodied in the relationship between backscatter data and the wall parameters, which can be obtained through the SVM training process. Measurement results reveal that once the training phase is completed, the technique only needs no more than one second to estimate wall parameters with acceptable errors. Then through-wall images are reconstructed using a back-projection (BP) algorithm by a finite-difference time-domain (FDTD) simulation. Noiseless and noisy measurements are discussed; the simulation results demonstrate that noisy contamination has little influence on the imaging quality. Furthermore, the feasibility and the validity are tested by a more realistic situation. The results show that high-quality and focused images are obtained regardless of the errors in the wall parameter estimates.

Highlights

Though-wall radar imaging (TWRI) is a form of nondestructive detection that has applications in civil engineering and security
In TWRI, if the wall parameters such as the wall thickness and the relative permittivity are known in advance, the changes in the speed and the amplitude attenuation of the electromagnetic waves that pass through the wall can be calculated accurately
Through-wall radar is similar to ground-penetrating radar (GPR), so we address through-wall problems using an support vector machine (SVM)

Summary

Introduction

Though-wall radar imaging (TWRI) is a form of nondestructive detection that has applications in civil engineering and security. In TWRI, if the wall parameters such as the wall thickness and the relative permittivity are known in advance, the changes in the speed and the amplitude attenuation of the electromagnetic waves that pass through the wall can be calculated accurately. Targets behind walls can be detected and located. There have been many studies on TWRI that have created highquality images with known wall parameters [1,2,3]. Wall parameters are generally not known a priori. If the wall parameters are not properly considered, the TWRI images will be fuzzy or distorted and the positions of the targets in the image will be incorrect

Methods

Results

Conclusion