Abstract: Task clustering in satellite observation scheduling can save resources and improve observing efficiency. A dynamic clustering scheduling algorithm (DCSA) is proposed to solve the scheduling problem of multi-satellites and multi-orbits. DCSA merges the clustering operation and the scheduling process dynamically, and uses a simulated annealing algorithm to search for a global optimization solution. The constraints of multi-task clustering are investigated with the prerequisite of satisfying the resolution requirements of clients, and the slew angle and time window of cluster-tasks are optimized. A clustering graph model is constructed, and the clique partition method of graph theory is applied to task clustering operation in the procedure of DCSA. Computation results demonstrate that DCSA is feasible and can effectively improve satellite observing efficiency.

Key words: satellite scheduling, dynamic clustering scheduling algorithm, task clustering, clique partition, simulated annealing algorithm