Radar Cross-Section (RCS) Estimation and Reduction

Abstract

The accurate prediction of radar cross-section (RCS) of various structures is crucial for controlling its visibility and hence plays a vital role in the development of stealth technologies. Several approaches like body geometry decomposition, low frequency techniques, high frequency techniques, and hybrid methods can be employed for RCS estimation based on the complexity of geometry and electrical size of the structure. Scattering entities especially electrically large ones give rise to a wide variety of electromagnetic phenomena like refraction, reflection, traveling waves, leaky waves, diffraction effects, etc. Although low frequency techniques provide accurate predictions for complex geometries, the computational complexity increases with electrical size of the structure. On the other hand, high frequency approaches, although computationally efficient for electrically large problems, give incorrect results when the problem under consideration has intricate geometrical features. Therefore, hybrid approaches incorporating both of them have been introduced to solve electromagnetic problems where neither class of formulations is sufficient by itself. This chapter presents an overview of these methods and certain case studies are also included for better clarity. Further, the popular approaches employed for reduction of RCS are also included with special emphasis on radar absorbing materials (RAM)/radar absorbing structure (RAS) and antenna array.