Image reconstruction for a partially immersed perfectly conducting cylinder using the steady state genetic algorithm

Abstract

[1] This paper presents a computational approach to the imaging of a partially immersed perfectly conducting cylinder by the steady state genetic algorithm. A conducting cylinder of unknown shape scatters the incident transverse magnetic (TM) wave in free space while the scattered field is recorded in free space. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived and the imaging problem is reformulated into an optimization problem. An improved steady state genetic algorithm is employed to search for the global extreme solution. Numerical results demonstrate that, even when the initial guess is far away from the exact one, good reconstruction can be obtained. Numerical results also show that the reconstructed image in the free space area is better than that in the medium area.

Image reconstruction for a partially immersed imperfectly conducting cylinder by genetic algorithm

“…In a typical GA, it uses the high crossover rate and mutation rate operator to generate all the new population in each new generation. On the contrary, SSGA only need to generate a few new population in each new generation (Johnson and RahmatSamii, 1997;Li et al, 2004). In other words, the number of fitness calculation corresponding to the new population is large in a typical GA compared with SSGA.…”

Inverse Scattering of an Un-Uniform Conductivity Scatterer Buried in a Three-Layer Structure

“…Owing to the difficulties in computing the Green's function by numerical method, the problem of inverse scattering in a three-layer structure has seldom been attacked. There are a lot of papers had used the genetic algorithm to solve the problems in many field [12][13][14][15][16][17][18], but there are few papers had applied the genetic algorithm to reconstruct the shape of a conductor [19][20][21][22][23]. However, to the best of our knowledge, there are still no numerical results by using the genetic algorithm for an un-uniform conductivity scatterer buried in a three-layer structure.…”

Image Reconstruction of the Buried Metallic Cylinder Using FDTD Method and Ssga

“…Most of the inversion techniques are investigated for the inverse problem using only single frequency scattering data (monochromatic source) [3][4][5][6][7][8][9][10]. However, the time domain scattering data is important for the inverse problem because the available information content about scatterer is more than the only single frequency scattering data.…”

“…Genetic algorithm (GA) [18] is well-known evolutionary algorithm of optimization strategy, which uses stochastic mechanism to search through the parameter space. In recent year, most of the researchers have applied GA together with the frequency domain EM solver for the inverse problems [4][5][6][7][8][9][10]. Fewer researchers had applied the genetic/evolutionary algorithms in the time domain inverse scattering problem for metallic target identification [19,20] and penetrable object reconstruction [21][22][23].…”

“…Interpolation technique through the closed cubic B-splines [26] is employed to describe a 2-D cylinder with arbitrary cross section more effectively. The inverse problem is formulated into an optimization one and then the non-uniform steady state genetic algorithm (NU-SSGA) [8] previously published by the authors is used to search the parameter space.…”