Cassini Radar Data: Estimation of Titan's Lake Features by Means of a Bayesian Inversion Algorithm

The analysis derived from the Cassini SAR imagery reflects the complex Titan's surface morphology with a wide range of backscattering coefficients and peculiar features such as periodic structures and lakelike features, which were observed on July 22, 2006, when polar areas were first imaged, and are considered good candidates to be filled with liquid hydrocarbons. In this paper, themodeling description of lakes is addressed bymeans of a double-layer model which considers an upper liquid-hydrocarbon layer and a lower layer compatible with the radar response of the neighboring areas. This model is introduced into a Bayesian framework for the purpose of inferring the likely ranges of some parameters and, in particular, of the optical thickness of the hypothesized liquid-hydrocarbon layer and of the wind speed. The main idea is to use the information contained in the parameter probability density function, which describes how probability is distributed among the different values of parameters according to the various scenarios considered. The analysis carried out on lakes and surrounding areas on flybys T16 and T19 determines optical thickness values from 0.2 to 6. For T25 flyby, the inferred values of optical thickness indicate that a limit value of optical thickness may be 9. Considering that, beyond these values, the signal from the bottom layer is completely attenuated, information on the wind speed on the upper layer can be inferred. The found mean values of wind speed are around 0.2-0.3 m/s according to different hypotheses on the upper layer dielectric constant.