Microwave Imaging of Parallel Perfectly Conducting Cylinders Using Real-Coded Genetic Algorithm

Abstract

Microwave imaging of parallel perfectly conducting cylinders in free space using real-coded genetic algorithm(RGA) is considered. The contours of the cylinders are denoted by shape functions which are approximated by trigonometric series. The direct problem is solved by point-matching method. RGA used in this paper is then introduced and the performance of it is investigated. The inverse problem is cast into a restrained optimization problem where the variables to be optimized are the coefficients of the trigonometric series; the object function is the relative error between the measured scattered electric field and the simulated one. The optimization problem is then solved by RGA. The validity of this method is demonstrated by some numerical examples. Some advantages and disadvantages of this method are discussed.