|Institution:||University of Washington|
|Full text PDF:||http://hdl.handle.net/1773/5986|
In the first part of the work, we developed coding for large-scale computation to solve 3-dimensional microwave scattering problem. Maxwell integral equations are solved by using MoM with RWG basis functions in conjunction with fast computation algorithms. The cost-effective solutions of parallel and distributed simulation were implemented on a low cost PC cluster, which consists of 32 processors connected to a fast Ethernet switch. More than a million of surface current unknowns were solved at unprecedented speeds. Accurate simulations of emissivities and bistatic coefficients from ocean and soil were achieved. Exponential correlation function and ocean spectrum are implementd for generating soil and ocean surfaces. They have fine scale features with large rms slope. The results were justified by comparison with numerical results from original code, which is based on pulse basis function, and from analytic methods like SPM, and also with experiments. In the second part of the work, fully polarimetric microwave emissions from wind-generated foam-covered ocean surfaces were investigated. The foam is treated as densely packed air bubbles coated with thin seawater coating. The absorption, scattering and extinction coefficients were calculated by Monte Carlo simulations of solutionsof Maxwell equations of a collection of coated particles. The effects of boundary roughness of ocean surfaces were included by using the second-order small perturbation method (SPM) describing the reflection coefficients between foam and ocean. An empirical wave-number spectrum was used to represent the small-scale wind-generated sea surfaces. The theoretical results of four Stokes brightness temperatures with typical parameters of foam in passive remote sensing at 10.8 GHz, 19.0 GHz and 36.5 GHz were illustrated. The azimuth variations of polarimetric brightness temperature were calculated. Emission with various wind speed and foam layer thickness was studied. The results were also compared with those based on Quasi-Crystalline Approximation (QCA).