Research On Robust Model And Algorithm For Mission Planning Of Networking Imaging Satellite

The mission planning of networking satellite presents the characteristics of a large scale of networking satellite, high requirement of imaging, time sensitive and many kinds of imaging resources and so on. Imaging satellite mission planning is widely affected by task inserting, task cancel, task property changing, weather conditions and other factors. The scheme planning under static environment can not satisfy the requirement of the robustness of scheme. In this context, it is the foundation and prerequisite of this study to establish scheme of imaging satellite mission planning with strong robustness, which is also the needs of imaging resource scheduling and project planning. In this paper, the specific work to solve the robustness of the networking imaging satellite mission planning is as follows:(1) In accordance with the process of imaging satellite task, the uncertainty factors are analyzed, and different strategies are adopted to satisfy the demand of robustness. According to the characteristics of various risk factors, the evidence theory is used to deal with the uncertainty of the mission of imaging satellite. At the same time, new robust indexes are sought to obtain the strong robustness of the execution sequence in the model solving process.(2) According to the actual demand of networking satellite mission planning, the robustness model is built with the risk factors. Symbolic representation and description is made in the process of establishing a robust programming model. According to the issue research problem, the robust model and objective function are constructed to satisfy the constraint condition.(3) To solve the NP-Hard problem of the model, this paper uses the improved genetic algorithm to solve the model. The new algorithm is based on genetic algorithm and simulated annealing algorithm. New algorithm is to adopt new chromosome form of solving problem, overcome the premature convergence and slow convergence problem, and apply more efficient evolutionary strategy.(4) Model simulation case experiment. In this paper, we use the simulation software STK tool kit to set up the corresponding scene. Planning scene contains a number of imaging satellites and the distribution of uniform ground targets. According to the construction of the robustness of the model, the model solution algorithm solves the scene planning. A case simulation example is given to analyze the planning scheme.