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Abstract
The Cassini spacecraft has obtained several backscatter observations of the surface of Titan at 2.18 cm-A.. We report the results of data reduction of various scatterometer observations of Titan. This work concentrates on the methodology of data reduction and processing for inference of surface parameters from Cassini-Titan backscatter experiments. We provide a detailed account of how the received raw echo samples are processed to ultimately yield surface the root-mean-square (RMS) slope and surface parameters. Using radar equation, the received backscatter power by Cassini RADAR is converted to monostatic radar cross section (RCS) measurements. The variation of RCS with the angle of incidence is then modeled using a linear superposition of a quasi-specular scattering law and the diffuse cosine law. from the parameters of the quasi-specular law, we obtain estimates for (RMS) slope of the surface and the dielectric constant of surface material. The latter allows us to conjecture about the composition of the surface. We use various quasi-specular models like Hagfors, Gaussian, and exponential models and a linear superposition of these like Gaussian plus Gaussian, Gaussian plus exponential, exponential plus exponential, Hagfors plus Hagfors, Hagfors plus Gaussian and Hagfors plus exponential models, where quasi-specular scattering is assumed to be effective below 20°, 25° or 30° . We determine the best model to fit our data according to the minimum residual. We deduce that the Gaussian plus exponential model provides the most accurate results. We compare the values of dielectric constant and RMS slope of the surface provided by each model. For example, the Gaussian plus exponential quasi-specular model gives a surface dielectric constant between 1.9 and 2.8. Dielectric constants between 2 and 3 are expected for a surface composed of solid simple hydrocarbons, water ice, or a mixture of both [12].