A5007337904- Planetary Science and Exploration
- Astro and Planetary Science
- Space Satellite Systems and Control
- Space exploration and regulation
- Space Exploration and Technology
- Geophysical and Geoelectrical Methods
- Geophysical Methods and Applications
- Underwater Acoustics Research
- Space Science and Extraterrestrial Life
- Inertial Sensor and Navigation
- Aerospace and Aviation Technology
- Advanced Sensor and Control Systems
Aerospace Information Research Institute
2024-2025
Chinese Academy of Sciences
2024-2025
State Key Laboratory of Remote Sensing Science
2024-2025
University of Chinese Academy of Sciences
2024-2025
China Aerodynamics Research and Development Center
2017
Chang’e-6 (CE-6) is the first sample-return mission from lunar farside and will be launched in May of 2024. The landing area south Apollo basin inside South Pole Aitken basin. Statistics analyses impact craters are essential to support safe geologic studies. In particular, crater size–frequency distribution information critical understanding provenance CE-6 samples returned can used verify refine chronology model by combining with radioisotope ages relevant samples. this research, a digital...
Photogrammetric mapping of large area the lunar surface using high-resolution orbiter images is very challenging due to increasing spatial resolution and lack a comprehensive understanding orbit error characteristics. The Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) are currently one highest-resolution Moon available. study LRO errors from perspective applications important for high accuracy areas NAC images. This paper proposes method estimation multi-coverage First,...
The Chang’e-6 (CE-6) landing area on the far side of Moon is located in southern part Apollo basin within South Pole–Aitken (SPA) basin. statistical analysis impact craters this region crucial for ensuring a safe and supporting geological research. Aiming at existing crater identification problems such as complex background, low accuracy, high computational costs, an efficient automatic detection model named YOLOv8-LCNET (YOLOv8-Lunar Crater Net) based YOLOv8 network proposed. first...