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室内散射测量系统与神经网络参数反演 被引量:2

Indoor scattering measurement system and retrieval of surface parameters using neural networks
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摘要 介绍了以矢量网络分析仪为核心的室内散射测量系统的组成、工作原理及其测量方法并利用该系统测量了不同含水量和不同粗糙度的裸土的微波散射系数。然后利用IEM模型计算的模拟数据作为人工神经网络的训练数据,用测量数据通过已训练的神经网络进行地表参数反演。结果表明室内散射系统的建立不仅有利于研究各种典型的地物微波散射机理,还为反演提供了所需要的数据。 Introduced the indoor scattering measurement system which was based on vector network analyzer and its working method.Using the system,microwave scattering coefficient of soil in a different moisture and roughness were measured.After that,using IEM model to calculate data as artificial neural network training data and choosing the Multi-angle dual-polarized structure to be trained so that to generate parameter inversion of network.Finally,put the measure data into the network to inversion parameter.Results show that Indoor scattering system is useful not only has the study the microwave scattering mechanism of surface featured,but also for the inversion to provide the required data.
出处 《电子测量技术》 2010年第9期35-38,共4页 Electronic Measurement Technology
基金 国家自然科学基金(40871160)
关键词 散射测量系统 散射系数 神经网络 IEM模型 S波段 scattering measurement system scattering coefficient neural networks IEM model S band
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