Simulation of Reflections from the Underlying Surface in an On-Board Radar with SAR

This study investigates the selection of suitable statistical models for speckle reflections from the underlying surface under low-altitude sensing conditions. A parametric approach to modeling speckle images of terrain fragments typical of synthetic aperture radar (SAR) is presented. We use a phenomenological model of speckle formation during radio wave interference, taking into account the spectrum of fluctuations, the roughness of the reflecting surface, the angle of incidence, and other radar parameters. We investigate the influence of the properties of the reflecting surface and the probing parameters on the nature of speckle images. The values of the sample cumulative coefficients for various multiplicative models of the reflection distribution are obtained. The properties and characteristics of various classes of distributions for describing the intensity and amplitude of speckles are considered: the gamma distribution, the K-distribution, and the classes of non-Gaussian probability densities G and G⁰. A generalized Gaussian (GG) distribution is used to model the complex components of reflected signals. We compare the obtained model characteristics with the sample characteristics of real terrain fragments in synthesized speckle images obtained by the on-board radar system. Based on a comparative analysis of cumulants, this paper examines methods for modeling amplitude and intensity speckle images using several classes of backscatter probability densities. Limitations in specific applications have been identified, and a modeling method using quadrature components has been developed in cases of extremely rough reflections.