A rapid decomposition method for remote sensing satellite missions based on the star-ground matching model

Autonomous task decomposition research in space is crucial. This paper proposes an approximate and analytical method for calculating time windows for point and small regional targets. It leverages satellite orbit patterns to establish models for sun-synchronous retrograde orbit distribution and satelliteground mapping, enabling rapid acquisition of time windows for point targets. Additionally, a boundary solving method based on slope-adaptive fitting is introduced for swiftly obtaining observation strips for regional targets. Simulation results show high precision and efficiency, with spatial-temporal errors at $\mathbf{0. 1 \%}$ and processing speeds in seconds, a significant improvement over traditional methods. This approach meets existing satellite platform requirements.