Efficient reconstruction of subsurface elliptical-cylindrical targets using evolutionary programming

Abstract

Evolutionary Programming (EP) optimization technique is proposed for efficient profile reconstruction and imaging of buried dielectric targets of elliptical-cylindrical shape. In particular, the efficiency of EP-based optimization in finding the location, shape, relative permittivity, and tilt-angle of the two dimensional (2-D) buried dielectric elliptical-cylindrical targets is investigated and statistically compared with Particle Swarm Optimization (PSO) method. Numerical results indicate that Evolutionary Programming method, as its first reported implementation in subsurface imaging, has a significantly better overall performance than PSO and can be used as a simple, yet efficient and robust global optimization technique for the inverse profiling of buried objects.