A New Method for Extraction of the Scattering Mechanism of Randomly Rough Surfaces Using Eigenvector Based Decomposition Technique

Abstract In this article, a statistical approach to evaluate distributed targets in a forward scattering problem is presented. Due to electromagnetic scattering, the scattered fields of a plane wave impinging upon randomly rough surfaces are usually affected by several parameters. In the surface remote sensing, the roughness criteria, such as ks and kl, play an important role in the scattering process. Whereas in synthetic aperture radar applications these parameters are stochastic; the use of the deterministic techniques, such as target decomposition, cannot be useful by itself as a tool of analysis. In these investigations, a statistical approach, namely the maximum-likelihood estimator, is essentially required to evaluate the target parameters including random variables. The goal of this article is the estimation of the polarimetric signatures, such as the scattering mechanism α and the entropy H, via a novel approach including the combination of target decomposition and the maximum-likelihood estimator. To validate our work, synthetic aperture radar data sets provided by the European Space Agency are analyzed and compared with the simulation results. These evaluations show that these signatures are estimated with an acceptable accuracy by means of the proposed technique.

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