自然土壤表面后向散射的蒙特卡罗模拟

遥感信息 Pub Date : 1997-08-03 DOI:10.1109/IGARSS.1997.615235

D. Casarano, F. Posa, Francesco Mattia, G. D. Carolis, J. Souyris, T. L. Toan, Guido Pasquariello

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引用次数: 1

摘要

本文的目的是研究多尺度粗糙度描述对地面雷达后向散射响应的影响。曲面是使用二维分数布朗运动过程生成的。采用基于Kirchhoff切平面近似的蒙特卡罗电磁模拟方法推导了后向散射系数。数值结果与IEM模型计算的后向散射系数进行了比较。考虑了指数函数、高斯函数和混合自相关函数。

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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Monte Carlo simulation of backscattering from natural soil surfaces

The objective of this paper is to investigate the impact of a multiscale roughness description on the surface radar backscattering response. Surfaces are generated using a 2D fractional Brownian motion process. A Monte-Carlo EM simulation based on the Kirchhoff tangent plane approximation is used to derive the backscattering coefficient. Numerical results are compared with backscattering coefficients obtained by means of the IEM model. Exponential, Gaussian and hybrid autocorrelation functions are considered.

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来源期刊

遥感信息

自引率

0.00%

发文量

3984

期刊介绍： Remote Sensing Information is a bimonthly academic journal supervised by the Ministry of Natural Resources of the People's Republic of China and sponsored by China Academy of Surveying and Mapping Science. Since its inception in 1986, it has been one of the authoritative journals in the field of remote sensing in China.In 2014, it was recognised as one of the first batch of national academic journals, and was awarded the honours of Core Journals of China Science Citation Database, Chinese Core Journals, and Core Journals of Science and Technology of China. The journal won the Excellence Award (First Prize) of the National Excellent Surveying, Mapping and Geographic Information Journal Award in 2011 and 2017 respectively. Remote Sensing Information is dedicated to reporting the cutting-edge theoretical and applied results of remote sensing science and technology, promoting academic exchanges at home and abroad, and promoting the application of remote sensing science and technology and industrial development. The journal adheres to the principles of openness, fairness and professionalism, abides by the anonymous review system of peer experts, and has good social credibility. The main columns include Review, Theoretical Research, Innovative Applications, Special Reports, International News, Famous Experts' Forum, Geographic National Condition Monitoring, etc., covering various fields such as surveying and mapping, forestry, agriculture, geology, meteorology, ocean, environment, national defence and so on. Remote Sensing Information aims to provide a high-level academic exchange platform for experts and scholars in the field of remote sensing at home and abroad, to enhance academic influence, and to play a role in promoting and supporting the protection of natural resources, green technology innovation, and the construction of ecological civilisation.