月球表层微波辐射模型及月壤厚度反演方法研究

发布时间：2018-03-09 08:12

本文选题：嫦娥一号　切入点：月壤厚度　出处：《华中科技大学》2011年硕士论文　论文类型：学位论文

【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。
[Abstract]:The acquisition of lunar soil thickness information is one of the important objectives of China's lunar exploration project. Its detection methods include direct and indirect methods. The microwave detector carried by Chang 'e-1 is based on lunar microwave radiation to detect lunar soil thickness information indirectly. Thus, the distribution of helium-3 resources throughout the month is estimated. This paper first introduces the existing monthly surface microwave radiation transfer model, analyzes the model and the selection of its parameters, and compares the measured brightness temperature in Apollo15 area with the simulated brightness temperature calculated by using the model, and analyzes the monthly surface parameters (temperature). The influence of Moon Shadow and rough Surface on the brightness temperature. In order to retrieve the lunar soil thickness from the measured light temperature of Chang 'e-1, the constrained optimization search method and the neural network method are used to study the inversion of the lunar soil thickness, and the inversion results are verified by combining with the Apollo region. The inversion thickness value is compared with the measured value. The results show that the monthly surface temperature is the main factor affecting the brightness temperature. In the low latitude area, the lunar shadow has a great influence on the high frequency bright temperature, and the influence of the rough surface on the bright temperature will directly lead to the error of thickness inversion. The search method based on constrained optimization and the thickness inversion based on neural network can reverse the reasonable thickness, but there is a certain gap between the thickness measured by Apollo and the measured thickness.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2011
【分类号】：P184.5

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