Abstract
Satellite task planning not only timetables the observation tasks to collect images of the earth surface, but also schedules the transmission tasks to download the images to the ground station for users using, it plays an important role in improving the efficiency of the satellite observation system. Satellite task planning is a typical combinatorial optimization problem and proved to be NP-Hard. However, the current works mainly schedule observation and transmission tasks in a separate way that ignoring the interaction between them on the resource (e.g. energy and memory) consumption and acquisition. In this paper, we analyze the single satellite observation and transmission tasks planning problem, then establish a directed acyclic graph model and propose a novel graph path search method with heuristics such as graph partition, resource usage estimation and rolling optimization to maximize the total benefit. Finally, the experimental results show the feasibility of our algorithm.
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