Time-Domain Inverse Scattering of a Two-Dimensional Metallic Cylinder in Slab Medium Using Asynchronous Particle Swarm Optimization

Abstract

Abstract-This paper presents asynchronous particle swarm optimization (APSO) applied to the time-domain inverse scattering problems of two-dimensional metallic cylinder buried in slab medium. For this study the finite-difference time-domain (FDTD) is employed for the analysis of the forward scattering part, while for the APSO is applied for the reconstruction of the two-dimensional metallic cylinder buried in slab medium, which includes of the location and shape the metallic cylinder. For the forward scattering, conceptually several electromagnetic pulses are launched to illuminate the unknown scatterers, and then the scattered electromagnetic fields around are measured. In order to efficiently describe the details of the cylinder shape, subgridding technique is implemented in the finite difference time domain method. Then, the simulated EM fields are used for inverse scattering, in which APSO is employed to transform the inverse scattering problem into optimization problem. By comparing the simulated scattered fields and the calculated scattered fields, the shape and location of the metallic cylinder are reconstructed. In addition, the effects of Gaussian noises on imaging reconstruction are also investigated.

Computational Approach Based on a Differential Evolution with Self-Adaptive Concept for Microwave Imaging of Two-Dimensional Inverse Scattering Problem

“…Moreover, it has been shown that PSO outperforms the real-coded GA in terms of convergence speed (Donelli & Massa, 2005). Some recent works have compared different algorithms in inverse scattering (Rekanos, 2008;Semnani et al, 2009;Pastorino, 2007;Rocca et al, 2009;Chiu & Hsiao, 2011;Sun et al, 2010b;Li et al, 2011). In 2006, DDE was first proposed to deal with the shape reconstruction of a conducting cylinder under the frequency domain (Qing, 2006).…”

Microwave imaging of buried dielectric cylinders by asynchronous particle swarm optimization

“…These algorithms based on strategies offer advantages relative to local inversion algorithms including strong search ability, simplicity, robustness and insensitivity to nonlinearity. Such as genetic algorithm (GA) [6]- [7], particle swarm optimization (PSO) [8]- [9], differential evolution/dynamic differential evolution (DE/DDE) [10]- [11] are proposed to search the global extreme of the inverse problems to overcome the drawback of the deterministic methods. However, these papers only focus on homogeneous dielectric cylinder or perfectly conducting cylinder cases.…”

Time Domain Inverse Scattering of Buried Inhomogeneous Dielectric Cylinders

“…In general, they tend to get trapped in local minima when the initial trial solution is far from the exact one. Thus, some populationbased stochastic methods, such as genetic algorithm (GA) [6][7][8][9]18], differential evolution (DE) [11,[19][20][21] particle swarm optimization (PSO) [12,13,[22][23][24][25], are proposed to search the global extreme of the inverse problems to overcome the drawback of the deterministic methods.…”