| In recent years,the number of on-orbit small-satellite constellations has been increasing rapidly.With the scale and complexity of mission planning problem becoming greater,the conflict between traditional mission planning methods and mission requirement is even severer.In this context,it is of great significance to carry out research on mission planning methods for small satellite constellations.Based on the summarization of related work at home and abroad,this dissertation,aiming the small satellite constellation mission planning problem,researches mission planning methods on problems with simple and complicated objective functions respectively.Work and innovation includes:1?Analysis of Mission Planning of Small Satellite Constellation The ground system of terrestrial observation satellites and space science satellite were introduced respectively.The similarities and differences of the two were compared and the task flow in ground application system was derived.The elements of the mission planning problem were analyzed,including the meaning and composition of tasks,resources,and constraints.Finally,the assumptions and simplifications of the problems adopted in this paper are introduced,and the process of solving the mission planning problem is summarized.2?Model and Algorithms of Constellation Mission Planning Problem under Simple Objective FunctionBased on the characteristics of the small satellite constellation,a suitable mission planning objective is proposed combined with a specific case in the practical application of small satellite constellation.The task planning elements and constraints of the constellation under simple objective function are analyzed,and the mathematical model of the mission observation planning based on pursuing the maximization of payload on-orbit working time is established.For small satellites,the storage capacity onboard is small thus the data downlink window has a great impact on the storage capacity.During the establishment of mathematic model,a dynamic storage resource constraint mechanism is established.By designing the corresponding implementation strategy as well as realizing it in the algorithm,the established model is closer to reality and the planning result is more reliable.For the established mathematical model,a greedy algorithm with objective function as a measure,and a genetic algorithm with strategies of task sequence integer coding and random decoding are designed.To avoid the loss of optimal solution,the elite retention strategy was introduced.The algorithm can further exert the global search ability of the genetic algorithm and avoid falling into the local optimal solution.Through the simulation case,the advantages and disadvantages of the two algorithms in dealing with such problems are analyzed,and the applicable scenarios of the two algorithms are summarized.3 ? Model and Algorithms of Constellation Mission Planning Problem under Complicated Objective FunctionA problem of multi-objective mission planning is proposed,aiming to shorten the user waiting time,reduce the planning failure goal,and improve the task assignment balance of satellites.To solve this problem,a genetic algorithm is used,which verifies the wide adaptability of the genetic algorithm.In order to solve its disadvantages of low efficiency,a simulated annealing algorithm was introduced.The powerful global search ability of genetic algorithm can help simulated annealing algorithm to avoid blind search,while simulated annealing algorithm's ability of efficient neighborhood search can reduce the number of cycles in genetic algorithm.The combined algorithms can effectively improve the efficiency of the solution.In this paper,the performance and effectiveness of several algorithms of the design are verified by simulation experiments.The results show that the algorithm strategy proposed in this paper can get satisfactory results on the corresponding scale issues.4?Further Consideration on Optimization of Mission Planning Methods for Small Satellite Constellation... |
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