| Summary: | 博士 === 國立中央大學 === 太空科學研究所 === 97 === ABSTRACT
In this dissertation, a new expression for a completed Kirchhoff field coefficient of the Advanced Integral Equation Model (AIEM) is re-derived. The comparisons of the bistatic scattering behavior by using the improved AIEM is in excellent agreement with numerical simulation and measured data, in terms of angular, frequency and polarization dependences. Based on this model, the transition model for AIEM is also proposed to improve the simulation accuracy. Validation by comparisons of the numerical method and experimental data gave good agreement. The second objective is to extend the AIEM for a fully polarimetric back-scattering matrix, called Stokes matrix. The Stokes matrix of AIEM includes all polarization correlation terms, and can be applied for the interpretation of the dependence on geophysical surface parameters, such as roughness, correlation length, and dielectric constant. Besides, for a wide range of use, the new scattering coefficient of AIEM for a rough surface with large heights is derived for practical applications.
The other objective of this dissertation is to develop a new surface class that can represent the real ground surface: It is the non-Gaussian correlated surface, namely the exponential-like surface class, with rms slopes and an adaptive ability for including high frequency spectral surface components. The validations of this new surface class are performed with calculations of backscattering and emissivity. Comparisons with different standard correlation functions and experimental data are given in this study.
Furthermore, the Dynamic Learning Neural Network (DLNN) is applied to perform the inversion of rough surface parameters. The estimation of soil parameters from polarimetric airborne SAR data (E-SAR) and multi-frequency SAR data (ALOS and ENVISAT) by using the AIEM are investigated. Results obtained for the new AIEM method are compared with other algorithm and demonstrate improved agreement.
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