Parameter estimation of non-Rayleigh RCS models for SAR images based on the Mellin transformation

The Mellin transformation-based method is developed to estimate the parameters of non-Rayleigh radar cross section (RCS) models for synthetic aperture radar (SAR) images from the observed image. Models investigated include heavy-tailed Rayleigh and Weibull. For each model, we consider the three kinds of images: intensity, square-root of intensity, and multi-look averaged amplitude. Using the Mellin transformation, we derive the analytical expressions of the first two second-kind cumulants for speckle and RCS respectively, and obtain the estimators according to the multiplicative model of SAR images and the Mellin convolution. Results of parameter estimation from Monte Carlo simulation and real SAR images demonstrate that the proposed estimators, which are easy to implement in the form of closed expressions, are efficient in estimating the parameters of non-Rayleigh RCS models from the observed SAR images.