| Title: | Bayesian analysis of noisy data: observations of the Moon with the ESA-Dresden 10 GHz radio telescope |
| Authors: | Tongtong Chen, Author |
| Material Type: | ISU Individual Project |
| Publisher: | Illkirch-Graffenstaden (France) : International Space University, 2019 |
| Size: | 1 electronic resource (xiv, 66 p.) / col. ill. |
| Bibliography note: | Includes bibliographical references |
| Languages: | English |
| Description: | Preparation for the extreme range of lunar surface temperature is essential for the success of robot and human exploration on the Moon. Much research about this topic has been carried out over the last few years. Generally, these approaches can be divided into three groups based on: the observation data, the theoretical model, and in-situ measurements. This paper presents a new Bayesian algorithm to measure the lunar surface temperature and analyze its periodical variation with respect to the Moon phases based on the observation data, which have been taken from ESA-Dresden 10 GHz Radio telescope. |
| ISU program : | Master of Space Studies |
| Permalink: | https://isulibrary.isunet.edu/index.php?lvl=notice_display&id=10699 |
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