Abstract
A systematic review is conducted on the research status and development trends of spacecraft Earth observation mission planning,aiming to ensure uniform task allocation and fuel/time efficiency during mission execution. Firstly,satellite Earth observation mission requirement planning technologies are introduced. Subsequently,modeling approaches and algorithms for spacecraft Earth observation mission planning are elaborated,with planning algorithms categorized into three groups:traditional optimization algorithms,intelligent optimization algorithms,and machine learning-based approaches. Detailed analyses are provided for different planning models and the three algorithm categories. Finally,development trends and future prospects for Earth observation mission planning technologies are discussed. Research in this domain provides theoretical foundations for engineering practices and technical support for applications including military surveillance,navigation planning,disaster management,and territorial mapping.
| Original language | English |
|---|---|
| Pages (from-to) | 1501-1518 |
| Number of pages | 18 |
| Journal | Yuhang Xuebao/Journal of Astronautics |
| Volume | 46 |
| Issue number | 8 |
| DOIs | |
| State | Published - 2025 |
Keywords
- Agile satellite
- Earth observation
- Intelligent optimization algorithm
- Machine learning
- Mission planning
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