An Optimization-Based Approach for Small Satellite Download Scheduling , With Real-World Applications

In this paper, we introduce a deterministic optimization model for scheduling downloads from satellites to Earth and then use our scheduling approach to analyze the QB50 mission (50 satellites and 50 ground stations). Given the large numbers of small satellites being launched into space, demand for downloading the large quantities of data acquired by each satellite has increased significantly. For a capacity-constrained ground station network, efficient scheduling can greatly improve the overall performance of satellite missions. Our approach maximizes the total amount of data downloaded from a satellite constellation while accounting for each satellite’s dynamics of collecting, storing, using, and spilling both data and energy. We test our model on simulated QB-50 data and report the results. We also use our model to evaluate various satellite capabilities and deployment options for the QB-50 mission. We find that each satellite could either reserve less of its energy for downloading data or collect and download approximately 25 times more data than what is currently planned. When the satellites do collect more data than what is currently planned, our scheduling approach enables up to 61% more of this data to be downloaded than a scheduling heuristic that reasonably approximates a current scheduling method.

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