Image reconstruction of impenetrable cylinders using cubic B-splines and genetic algorithms

We discuss a new method for the shape reconstruction of perfectly conducting cylinders from measured data based on cubic uniform B-splines and genetic algorithms. The perimeter of the cylinder is modeled by cubic B-splines. A B-spline is defined by an ordered set of control points which determine the shape of the corresponding curve. With an appropriate choice of control points, smooth curves as well as sharp edged contours can be modeled. The direct and inverse problems are formulated. We present sample test results obtained by applying the proposed inversion algorithm to real experimental data. Both principal polarizations (TM and TE) are treated separately and in combination depending on the availability and the nature of the measured data. The performance and limitations of the inversion algorithm on full as well as limited angular views are discussed in detail. It is shown that the proposed method is less sensitive to noise than those using Fourier expansions (see Chiu, C.-C. and Liu, P.-T., 1996).