Research On Cooperative Mission Planning Of Earth Observation Satellite Cluster

With the rapid development of space technology,the number of earth observation satellites is increasing,and their functions are gradually enhanced,which can quickly complete more different types of observation tasks.The emergence of agile earth observation satellites,which can quickly complete the three-axis maneuver,makes the task execution scheme more flexible.When multiple ground targets are distributed intensively in a certain area,it is difficult for a single satellite to observe all targets.It is necessary to plan the task sequence reasonably to obtain higher observation benefits.The cluster of satellites maintained by multiple satellites flying in the near space region can complete the observation of more targets in the region.How to make reasonable use of satellite resources,so that multiple satellites can cooperate with each other to achieve the goal of higher total income has become an important research trend.Aiming at the maneuverability and working mode of agile earth observation satellite,the satellite dynamic model and observation task model are established.Firstly,the orbit prediction method considering J2 long term perturbation is proposed by using orbit elements.Considering the capability of three axis maneuver of agile satellite,the attitude determination method and the calculation method of task switching time are proposed.In view of the performance of the earth observation satellite,a constraint satisfaction model considering multiple constraints is established.The additional pitch axis maneuverability of agile satellite makes the execution time of observation task more flexible.This paper proposes an observation time window selection planning based on revenue density.Firstly,a task planning method based on ant colony algorithm is proposed for a single satellite,and then the ant colony algorithm is improved so that it can be used in multi satellite cooperative task planning.For multitype observation tasks,this paper decomposes and unifies complex tasks,which makes it suitable for task planning algorithm.Because of the time-effective requirements of the earth observation task planning,the traditional optimization algorithm is difficult to use in orbit task planning because of its long calculation time.This paper proposes a method of satellite in orbit Autonomous Task Planning Based on the theory of reinforcement learning.The decision-making network obtained by ground training can be used for on orbit mission planning,and a better scheme can be obtained on the basis of ensuring timeliness.Then,considering the ability of inter satellite information interaction,the Multi-Agent Reinforcement Learning Theory is used to propose a distributed satellite multi satellite cooperative task planning method.