Statistical Characterization of Random Rough Surfaces Using the Tilt Modulationof the Backscatter Radar Cross Sections: Full Wave Approach

摘要

In order to evaluate the like and cross polarized cross sections of random roughsurfaces it is necessary to characterize the surface by their height and slope joint probability density functions. A broad class of rough surfaces can be characterized by a family of gamma functions of order K. The marginals of these joint surface height probability density functions include the exponential and the Gaussian surface height probability density functions in the limits for K = 1 and K approaches limit of infinity, respectively. In this reprint, we consider the feasibility of using Synthetic Aperture Radars (SAR's) to determine the statistical characterization of the random rough surfaces. The unified full wave approach, which accounts for scattering from composite rough surfaces with a broad range of roughness scales, is used to compute key elements of the Stokes matrix. These computations are used to derive the like and cross polarized radar backscatter cross sections arbitrarily oriented SAR resolution cells (pixels) and the associated cross section modulation for tilts in and perpendicular to the plane of incidence. (Author) (kr)