Mission Planning for LEO Satellite IoT Constellation Based on Genetic Algorithm - Yanhong LI; Qiang LYU; Junmin LIANG; Shigang FENG; Junhou MIAO (天地一体化信息网络)
A mission planning algorithm based on genetic algorithm was designed for LEO satellite IoT constellation with no inter-satellite links, aimed to achieve real-time data communication through multiple ground stations while maximized the resource allocation of satellites and ground stations.Firstly, the objective function to maximized the service duration of satellites in orbit and the constraints on clashed tasks were designed, constructed the mission planning model for LEO satellite IoT constellation.Then, based on genetic algorithm, clashed tasks and early stopping mechanism were introduced, and the mission planning algorithm for the LEO satellite IoT constellation was designed.On this basis, experiments were conducted use a constellation of 18 LEO communication satellites without inter-satellite links and 4 ground stations.In addition, in order to verified the performance of the algorithm, first come first service (FCFS) algorithm was also used for mission planning of the experimental data.The experiments compared with FCFS showed that the designed mission planning algorithm for LEO satellite IoT constellation could significantly improve the scheduling capacity of ground stations for receiving data of communication satellites, addressed the contradiction of insufficient ground stations with a large number of satellites.