A new multilayer model for the investigation of lunar regolith depth

Mingxing Zhou; Jianjiang Zhou; Fei Wang; Xiao Zhang

doi:10.1117/12.832283

30 October 2009 A new multilayer model for the investigation of lunar regolith depth

Mingxing Zhou, Jianjiang Zhou, Fei Wang, Xiao Zhang

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74980B (2009) https://doi.org/10.1117/12.832283
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Passive microwave remote sensing was firstly applied to detect the moon by Chang'E-1 satellite with a four channel microwave radiometer. Its primary goal is to detect the thickness of lunar regolith and to assess the content of ³He. There are remained theoretical problems to be systematically solved, which include to research the microwave radiation transfer properties and to establish the suitable model to inverse lunar regolith depth. Considering the variation of these factors influencing on the brightness temperature, a new multi-layer microwave transfer model to inverse the depth of lunar regolith is presented. The physical factors among top lunar regolith influencing the brightness temperature change sharply with the thickness, so the top lunar regolith is divided subtly. On the contrary, the deep lunar regolith where the factors vary slowly with the thickness is divided roughly. Then, by applying the fluctuation dissipation theorem, the brightness temperatures obtained from four frequency channels (3.0GHz, 7.8GHz, 19.35GHz, 37GHz) are simulated based on the multi-layer model at different locations on the moon and at different times of a lunar day. In comparison the calculated results with other models, it indicates that the proposed model has better stability and less calculation.

Citation Download Citation

Mingxing Zhou, Jianjiang Zhou, Fei Wang, and Xiao Zhang "A new multilayer model for the investigation of lunar regolith depth", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74980B (30 October 2009); https://doi.org/10.1117/12.832283

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