Multiband Microwave Sensing for Surface Roughness Classification

Philipp A. Scharf, Johannes Iberle, H. Mantz, T. Walter, Christian Waldschrnidt
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引用次数: 3

Abstract

This contribution presents an approach for frequency dependent surface roughness classification algorithms. For both simulations and measurements of the backscattering on random rough surfaces statistically defined surfaces were synthesised as well as manufactured. The coexistence of quasi-identical real and model surface profiles enables the validation of scattering models. The Fresnel-Kirchhoff diffraction theory will be applied and compared with a full-wave simulation software as a reference followed by measurements in the E and D band. Frequency dependency and roughness scaling effects will be worked out to derive a model-based methodology for the estimation of roughness depths as it is needed for applications like road condition detection.
用于表面粗糙度分类的多波段微波传感
这一贡献提出了一种基于频率的表面粗糙度分类算法。为了模拟和测量随机粗糙表面上的后向散射,我们合成并制造了统计定义表面。准相同的实际和模型表面轮廓的共存使得散射模型的验证成为可能。将应用菲涅耳-基尔霍夫衍射理论,并与全波模拟软件作为参考进行比较,然后在E和D波段进行测量。频率依赖关系和粗糙度缩放效应将得到一个基于模型的方法来估计粗糙度深度,因为这是道路状况检测等应用所需要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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