RCS reduction of canonical targets using genetic algorithm synthesized RAM

Abstract

Radar cross section (RCS) reduction of canonical (planar, cylindrical, and spherical) conducting targets is the focus of this paper. In particular, a novel procedure is presented for synthesizing radar absorbing materials (RAM) for RCS reduction in a wide-band frequency range. The modal solutions of Maxwell's equations for the multilayered planar, cylindrical, and spherical canonical structures is integrated into a genetic algorithm (GA) optimization technique to obtain the best optimal composite coating. It Is shown that by using an optimal RAM, the RCS of these canonical structures can be significantly reduced. Characteristics of bistatic RCS of coated cylindrical and spherical structures are also studied and compared with the conducting structures without coating. It is shown that no optimal coating can be found to reduce the RCS in the deep shadow region. An in-depth study has been performed to evaluate the potential usage of the optimal planar coating as applied to the curved surfaces. It is observed that the optimal planar coating can noticeably reduce the RCS of the spherical structure. This observation was essential in introducing a novel efficient GA with hybrid planar/curved surface implementation using as part of its initial generation the best population obtained for the planar RAM design. These results suggest that the optimal RAM for a surface with arbitrary curvature may be efficiently determined by applying the GA with hybrid planar/curved surface population initialization.