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Lunar Surface Microwave Radiative Transfer Model and Lunar Regolith Depth Retrieval Method Research

Author: DuXiaoSai
Tutor: GuiLiangQi；LiQingXia
School: Huazhong University of Science and Technology
Course: Electromagnetic Field and Microwave Technology
Keywords: CE-1 lunar regolith depth microwave transfer model lunar surface shadow effect constraint optimization search method neural network
CLC: P184.5
Type: Master's thesis
Year: 2011
Downloads: 31
Quote: 1
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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.

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CLC: > Astronomy,Earth Sciences > Astronomy > Solar system > Moon > The lunar surface physics and methods of observation
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