An Efficient Graph-Based Approach for Periodic Earth Observation Over the Satellite Networks

Periodic observation is widely used for information collection in emergency scenarios such as earthquakes, wildfires, and floods. Multi-satellite observation is needed to achieve pe-riodic observation due to the limited observation capability and long revisit period of a single satellite. Choosing when and which satellite to observe the target to achieve periodical observation can be challenging. Existing efforts adopt a time-consuming method to solve the problem. They also ignore some feasible solutions. Moreover, the classical mathematical programming method can also take a long time to solve the problem. Therefore, we propose a graph-based periodic scheduling method. First, we formulate the problem as a Mixed-Integer Linear Programming (MILP) problem, which is non-convex and intractable. To address this, we introduce a periodic observation graph model that transforms the original problem into a path-finding problem. We then propose a graph-based periodic observation path construction algorithm. Numerical simulations under the settings of a realworld satellite network demonstrate that the performance of our scheme is significantly faster than the baselines and can obtain observation offsets.