【作者】 杜小赛；

【导师】 桂良启； 李青侠；

【作者基本信息】 华中科技大学 ， 电磁场与微波技术， 2011， 硕士

【摘要】 获取月壤厚度信息是我国探月工程的重要目标之一,其探测方法包括直接和间接两种方法,嫦娥一号搭载的微波探测仪是基于月球微波辐射间接地探测月壤厚度信息,从而估算全月的氦-3资源的分布。本文首先介绍目前已有的月表微波辐射传输模型,对模型及其参数的选择进行分析,并将Apollo15地区的实测亮温与利用模型计算的模拟亮温进行比较,分析了月表参数(温度、月球阴影及粗糙表面)对亮温的影响。为了从嫦娥一号实测亮温反演月壤厚度,本文分别使用约束最优化搜索方法和神经网络方法进行厚度反演研究,并结合Apollo地区进行反演验证,将反演厚度值与实测值进行对比。分析结果表明月表温度是亮温影响的主要因素,在低纬地区,月球阴影存在的情况下,对高频的亮温影响很大;粗糙表面对亮温的影响会直接导致厚度反演的误差变大;基于约束最优化搜索方法和神经网络的厚度反演能够反演出合理的厚度,但与Apollo实测厚度有一定差距。更多还原

【Abstract】 One of the important aims of the lunar exploration is to detect the lunar regolith depth, including direct way and indirect ways. The microwave radiometer carried on the CE-1 is a indirect way to detect the surface temperature, dielectric constant and the heat flow information of the lunar surface. The final purpose is to retrieve the lunar regolith depth and then evaluate the full moon He-3 distribution.This paper introduces the existing lunar surface microwave transfer models, and compares the models from the layer and parameter selection. The brightness temperatures simulated from the models are compared with the brightness temperature measured by CE-1 at the Apollo 15 area. Then the lunar surface parameters’ influence on the brightness temperature is analyzed, such as the temperature, lunar shadow effect and the rough surface.In order to retrieve the lunar regolith depths from the measured brightness temperature, the constraint optimization search method and neural network method are studied. Considering the parameters at the Apollo area are sufficient, the Apollo area is chosen to evaluate the lunar regolith depth retrieval method.The results show that the lunar surface temperature is the main factors affecting the brightness temperature. At the low latitude area, when the lunar surface shadow area is obvious, the shadow effect to the high frequency brightness temperature should be considered. The brightness temperature influenced by the rough surface can directly lead to the error of the retrieval lunar regolith depth become greater. Though the lunar regolith depths retrieved form constraint optimization search method and the neural network at the Apollo area are in the rational limits, compared with the measured regolith thickness, the differences are obvious.更多还原