Dielectric objects reconstruction by combining subspace-based algorithm and randomly global optimization algorithm

Abstract

This paper discusses an inverse scattering problem for the reconstruction of permittivity distribution of two-dimensional dielectric objects. 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. We solved the problem by combining subspace-based algorithm and self-adaptive dynamic differential evolution (SADDE). SADDE can process numerous unknowns of electromagnetic imaging problems. Different scatterers and environment have used to verify the stability of subspace-based algorithm and SADDE. We also compare genetic algorithm (GA) to show the robustness and the searching speed of SADDE. Numerical results show that the permittivity distribution of the dielectric objects is well reconstructed by SADDE.

Keywords:

• Inverse scattering
• subspace-based algorithm
• self-adaptive dynamic differential evolution