No abstract

Two techniques for the shape reconstruction of multiple metallic cylinders from scattered fields are investigated in this paper, in which two-dimensional configurations are involved. After an integral formulation, the method of moment (MoM) is applied to solve it numerically. Two separate perfect-conducting cylinders of unknown shapes are buried in one half-space and illuminated by the transverse magnetic (TM) plane wave from the other half space. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equation is derived and the imaging problem is reformulated into optimization problem. The non-uniform steady state genetic algorithm (NU-SSGA) and asynchronous particle swarm optimization (APSO) are employed to find out the global extreme solution of the object function. Numerical results demonstrate even when the initial guesses are far away from the exact shapes, and the multiple scattered fields between two conductors are serious, good reconstruction can be obtained. In addition, the effect of Gaussian noise on the reconstruction results is investigated and the numerical simulation shows that the reconstruction results are good and acceptable, as long as the SNR is greater than 20 dB.

A time-domain inverse scattering technique for estimating the location, shape, and permittivity of a dielectric cylinder in a slab medium is proposed. In this paper, the finite-difference time domain is employed for the analysis of the forward scattering part, and asynchronous particle swarm optimization (APSO) is applied for the reconstruction of the two-dimensional homogeneous dielectric cylinder. For the forward scattering, several electromagnetic pulses are launched to illuminate the unknown scatterers, and then the surrounding scattered electromagnetic fields are measured. In order to efficiently describe the details of the shape, a sub-gridding technique is implemented in the finite-difference time domain method. Then, the simulated electromagnetic fields are used for inverse scattering, in which APSO is employed to transform the inverse scattering problem into an optimization problem. APSO is a population-based optimization approach that aims to minimize a cost function between measurements and computer-simulated data. The numerical results presented for the two examples of scatterers under transverse-electric incidence demonstrate that the proposed method is capable of reconstructing a complicated shape with a rapid rate of convergence and robust immunity to noise.

No abstract

No abstract