Aspects of model-based decompositions in radar polarimetry

In this paper, we further analyse the problem that polarimetric target decomposition methods in general have more physical parameters than equations, making the decomposition under-determined and hence have no unique solution. The common approach to get around this problem is to make certain assumptions, thus fixing one or more parameters, allowing the other free parameters to be solved from the set of expressions. We recently showed how to obtain additional information from fourth-order statistics to find a unique solution to model-based polarimetric decompositions ([1]). We previously showed a fourth-order unique solution that was valid only for Gaussian data, and indicated that non-Gaussian data led to an over-estimation in many of the parameters. This work describes our new method to obtain a generic textured data solution through an optimisation approach and presents preliminary results for a sea ice specific model.