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Reconstruction of Two-Dimensional Randomly Rough Surfaces Based on Bidirectional Reflectance Distribution Function

机译:基于双向反射分布函数的二维随机粗糙表面重构

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摘要

This article presents an inverse method for reconstructing two-dimensional randomly rough surfaces based on the available (experimental or given) data of the bidirectional reflectance distribution function (BRDF). The Maxwell's equations of electromagnetic waves are applied to describe the light scattering process of rough surfaces by accounting for the near-field effect. Such a forward problem is numerically solved with the finite-difference time-domain algorithm. The inverse scattering problem of reconstructing the surface profile is handled by means of an optimization technique - the particle swarm optimizer algorithm. As an example, reconstruction of a Gaussian rough surface is conducted based on the experimental data of BRDFs. The retrieved results of the surface profile are compared with those measured by atomic force microscopy from the samples, which shows that the reconstruction algorithm can provide the credible prediction of surface profiles. The reconstruction approach studied in this study can make reliable predictions of the actual or required surface profiles.
机译:本文提出了一种基于双向反射率分布函数(BRDF)的可用(实验或给定)数据重建二维随机粗糙表面的逆方法。通过考虑近场效应,采用电磁波的麦克斯韦方程来描述粗糙表面的光散射过程。用有限差分时域算法在数值上解决了这种前向问题。重建表面轮廓的逆散射问题是通过优化技术-粒子群优化算法来解决的。例如,根据BRDF的实验数据进行高斯粗糙表面的重建。将表面轮廓的检索结果与通过原子力显微镜从样品中测得的结果进行比较,表明重建算法可以提供可靠的表面轮廓预测。在这项研究中研究的重建方法可以对实际或所需的表面轮廓进行可靠的预测。

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