Mission Planning for Agile Earth Observing Satellite Based on Genetic Algorithm

A new method based on genetic algorithm and a new model are presented in this paper to solve the mission planning problem for Agile Earth Observation Satellite at multiple observation points. Firstly, a new mission planning model is established by considering various physical constraints of satellite and ground targets, and a novel performance function with multi-objective observation profits and attitude maneuvering energy consumption taken in account is designed. Then, the genetic algorithm’s fitness function is determined by the performance function, a new method for calculating the fitness function is proposed based on time constraints, and the observation sequence is numerically coded. The observation sequence and the observation time are derived by genetic algorithm. Finally, simulation experiments are carried out with several Chinese cities as the observation targets. The experimental results verify the feasibility and efficiency of the proposed method.