Research on lunar regolith of the Chang'E-4 landing site: An automated analysis method based on deep learning framework

Abstract

On January 3, 2019, the Chang'E-4 lander successfully landed within the Von Kármán crater, located in the South P ole-Aitken Basin (SPA) on the farside of the Moon (45.5°S, 177.6°E), marking the first soft landing on the lunar farside. The lander, equipped with the Lunar Penetrating Radar (LPR) system, aimed to provide insights into the structure and evolution of the Moon. Previous research often relied on manually identifying hyperbolic features to analyze the lunar shallow subsurface properties. This inefficient approach may lead to subjective biases, resulting in unstable outcomes. This research constructed an automatic analysis framework by integrating the Swin Transformer with a 3D velocity spectrum, which is then applied to analyze the properties of the Chang'E-4 LPR data. The experimental results indicate that the framework achieved a precision of 98.9 % and a recall of 96.7 % in hyperbolic feature identification, with an $F_1$ of 0.9782 and AP of 94.8 %. Additionally, it has been experimentally validated that the framework can accurately invert hyperbolic features' two-way travel time and velocity. Finally, the framework is applied to analyze the lunar shallow subsurface structure and properties within the landing area of the Chang'E-4 mission.