Hybrid of genetic algorithm with particle swarm optimization to shape reconstruction of perfect conducting cylinders

Abstract

Abstract In this study, the shape reconstruction of conducting cylinders by making use of electromagnetic scattered fields is presented. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived and the imaging problem is reformulated in to an optimization problem. A hybrid evolutionary algorithm suitable for the optimization of large-domain electromagnetic problems is proposed for the solution of the inverse scattering problem arising in microwave-imaging applications. The hybrid technique, called genetical swarm optimization (GSO), combines genetic algorithms (GA) and particle swarm optimization (PSO). In such a framework, this paper is aimed at assessing the effectiveness of the proposed approach in locating and shaping of unknown two-dimensional perfect conducting cylinders. Reconstructions of conducting scatterers from experimental inverse scattering data are finally presented to demonstrate the accuracy and efficiency of the hybrid technique.