Research On Key Problems Of Agile Satellite Imaging Scheduling Problem

Obtaining high spatial resolution and high temporal resolution, hyperspectral imaging data has been strategic needs of supporting national economic construction and protecting national security. With its mobile,flexible features,agile satellite equipped with high-resolution sensors can meet the strategic needs,greatly improving the service capacity and efficiency of the spacecraft.Research and launch of agile satellite is an important turning point in Chinese aerospace industry.Agile satellite has a fast and stable imaging capability of revolving on any euler axis(including roll, pitch, yaw). Agile satellite can complete complex remote sensing imagery flight, including customized imaging of multiple spot targets on the single orbit,multiple bands splice imaging of large regional target on the single orbit,multi-view stereo imaging of the same target on the single orbit,and push-broom imaging of the target of non-along-track direction on the single orbit.According to mission requirements,how to develop a scientific, precise scheduling strategy that is used for the high-speed operation satellite in orbit completing the above mentioned complex maneuver combined action and achieving the technical problems of getting high spatial resolution and high temporal resolution images,which has been a key issue of scheduling technology research of agile satellite home and abroad.To best meet the needs of users and improve the overall effectiveness of agile satellite system, in this paper, the sudy is fouced on the key issue of agile satellite scheduling technology and divided into the following three aspects:imaging tasks pretreatment, scheduling model and the optimizing algorithm. Specific contents are as follows:(1) In this section,satellite imaging principles were intensively studied, from the perspective of agile scheduling,orbital characteristics of remote sensing satellite platforms, the control of agile attitude and the principle of the imaging sensor were analyzed; four typical working modes of agile satellite were presented in summary. Agile satellite imaging mode enhances the scheduling flexibility and the possibility of completing complex tasks of agile satellite.In the four aspects of optimization goal, imaging tasks, satellite resources and constraints, the agile satellite scheduling problem was comprehensive described. Based on the above, the basic input and output elements of problem were summarized.(2) Pretreatment methods for complex tasks were studied. For large regional targets, we proposed a dynamic decomposition method for regional goals of agile satellite. The method considers the actual situation that satellite swath changes depending on the satellite observing angle, calculates the observing angle, swath, and strip duration of agile imaging satellite dynamically based on STK software, proposed a dynamic decomposition method cutting area target using parallel strip of dynamic swath and provided a calculation model of the minimum agile satellite attitude transition time. On this basis, a certain step-size search algorithm is designed for finding the best observation point of agile imaging satellite towards area target. For dense point target, using task clustering strategy.Pitch, side swing of agile satellite task clustering and transition time constraints between agile satellite tasks were analyzed. Clustering graph model was established, and its construction algorithm was given.The task clustering was converted into clique partitioning problem and a clique partition clustering algorithm based on heuristic rules was proposed. After pretreatment, the above-mentioned complex tasks were unified descriped as atomic tasks that are strips.(3) For French SPOT5 satellite imaging scheduling problem, using a weighted constraint satisfaction problem model, the hybrid discrete particle swarm optimization algorithm was proposed, which is able to handle constraints. The local neighborhood topology was introduced to avoid premature convergence. At the same time, a local search strategy was introduced to improve the local search ability.On the aspect of constraints handling,a fuzzy repair plus penalty function strategy was proposed.Benchmark problem experimental results show that the algorithm used to solve French SPOT5 satellite imaging scheduling problems is feasible and effective.(4) The optimization model based on the time constraint network of agile imaging satellites scheduling problem was established.Based on the traditional non-agile satellite scheduling model, the model introduced time constraints, and the constraint satisfaction problem was transformed into constrained optimization problem; the optimization algorithm based on neighborhood search was proposed. Global search capability of GA and local optimization capabilities of Tabu Search was integrated into the algorithm. Four neighborhood structure and crossover were designed, they are executed alternately during the search process.Infeasible solution was allowed but punished. Experiment results showed the effectiveness of the algorithm.