An approach of satellite periodic continuous observation task scheduling based on evolutionary computation

The observation task scheduling of Earth Observation Satellites (EOSs) is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that one target only need to be observed once. However, with the development of remote sensing data applications, some new observation requests appear, which need EOSs take image to a target periodically. Considering the characteristic of the problem, a constraint satisfaction problem model with two objective functions is established. Furthermore, a satellite periodic continuous observation task scheduling algorithm based on multiobjective evolutionary algorithm is proposed. Finally, some experiments are implemented to validate correctness and practicability of our algorithm.