Multi-sensor analysis of Titan surface: SAR and radiometric data synergy for estimating wind speed and liquid optical thickness of hydrocarbon lakes

摘要

In this work, scattering models and a Bayesian inversion algorithm are applied to Cassini SAR and radiometric data in order to characterize lake and land surfaces. Radar backscattering from lakes is described in terms of a double layer model, Bragg or facets scattering for the upper liquid layer and I.E.M model for the lower solid surface. This electromagnetic analysis is the starting point for the statistical inversion algorithm, to determine limits on the parameters values. Radiometer data are described with a forward radiative transfer model thus accounting for the presence of multiple layer emission and volume effects. A combined sensitivity study is performed on backscattering and brightness temperature models to define the best approach for the synergic use of active and passive data in the Bayesian algorithm. The use of e.m. scattering models allows evaluating the compatibility of the observed RCS with the expected scenarios in terms of dielectric constant of the surface constituents. A good correlation is found between the radar and the radiometric data. Brightness temperature modeling combined with SAR Bayesian inversion can improve parameter retrieval.