【作者】 项军华；

【导师】 张育林；

【作者基本信息】 国防科学技术大学 ， 航空宇航科学与技术， 2007， 博士

【摘要】 星座构形设计是星座部署和运行的前提。星座部署和运行的性能要求是影响星座构形设计的重要性能指标。论文针对星座构形与运行维持性能要求的相互影响,分别对卫星星座的摄动补偿策略、构形控制、空间备份策略、以及区域导航星座和分阶段部署导航星座的优化设计等问题进行了研究。通过分析卫星星座的基本轨道以及星座构形基本约束,建立了星座基本构形和状态描述模型。研究了星座几何构形与运行维持性能的关系,包括星座构形的最大容许漂移量、长期稳定性、性能台阶、容错性以及可扩展性等。通过分析卫星轨道、星座构形和星座性能的稳定性,设计了星座构形优化设计的参数偏置摄动补偿策略,通过摄动补偿的方法对星座构形参数进行优化设计,提高了星座构形稳定性,并且分析了摄动补偿策略的适应条件和范围。分析了星座构形控制的特点和过程,明确了星座构形控制任务。基于覆盖性能要求进行了星座构形最大容许漂移量的计算。提出了分段离散序列控制策略并将其应用于星座构形设计。针对星座故障或失效卫星的存在问题,提出了相邻相位和均匀相位的星座构形沿航迹重构控制策略,建立了考虑燃料消耗、重构时间、燃料消耗均匀性、性能修复程度综合最优的星座构形变换优化准则,实现星座构形沿航迹失效重构。以天基多基地雷达星座为背景,进行了区域覆盖星座构形和控制策略优化设计研究。从提高备份卫星可用性的角度进行备份轨道的选择和设计,建立了星座空间备份策略设计性能模型,提出了基于卫星可靠度和平均修复时间的星座空间备份策略优化设计方法。基于区域导航星座的GEO/IGSO/MEO基本结构,考虑区域导航星座设计的基本需求和约束,建立了星座设计优化数学模型,基于多岛遗传算法优化策略进行多目标多约束条件下区域导航星座全局优化设计,得到了多个满足任务需求的设计方案。针对区域导航星座扩展性能要求进行了基于基准构型的区域导航星座扩充优化设计。结合区域导航星座任务特点,基于摄动补偿策略对星座构形进行了优化设计,提高了星座构形稳定性。分析了导航星座部署的阶段性特点,设计了分阶段部署导航星座基本结构,明确了分阶段部署导航星座设计目标和与约束,建立了分阶段部署导航星座优化设计模型,综合考虑星座构形长期稳定性、构形控制、系统可靠性、系统费用、部署策略、备份策略等性能约束并结合我国导航星座实际任务需求,基于多目标进化算法的优化策略和线性加权和法的多目标决策进行了分阶段部署导航星座的多目标优化设计。更多还原

【Abstract】 The constellation design is the premise of the deployment and the operation of satellite constellation, and the performance requirements on the deployment and the operation of satellite constellation are the important factors that affect the constellation design. Considering the constraint relations between the configuration and the operation of satellite constellation, the optimization design problems are studied on the perturbation compentation strategy, the configuration control, the spatial backup strategy, the regional coverage navigation constellation and the staged deployment navigation constellation.The basic orbits of satellite constellation and the basic restraints of constellation configuration are analyzed, and the basic configuration models and the state description models for satellite constellation are established. The relationships between the constellation geometry configuration and the performance of the operation and maintenance are studied, which include the allowable drifting most greatly, the long-term stability, the performance stair, the fault tolerance as well as the extendibility demand for constellation configuration.The stability of the satellite orbit, the constellation configuration and performance is analyzed. Based on the active deviation of the orbital parameters, the compentation strategy on the perturbation is designed, then the configuration optimaztion for the constellation using the compenstation strategy is finished, and the configuration stability of the satellite constellation is improved, and its suitable conditions and scopes also are analyzed.The characteristics and the process of the constellation configuration control are analyzed, and the control missions of the satellite constellation are determined. Based on the coverage performance requirements, the allowable drifting most greatly of the constellation configuration is computed. The partition separate sequence control strategy is presented, and applies it in the design of the constellation configuration. In view of the problems about the satellite breakdown or the satellite expiration, the reconfiguration control strategies including the neighboring phase and the even phase of the constellation configuration along-track are presented. The most superior constellation configuration transformation optimization criterions are established that the criterions considered the fuel consumption, the reconfiguration time, the fuel consumption uniformity and the performance repaired and all so, and the constellation configuration along-track expiration reconfiguration is realized. Take the space borne multistatic radar constellation as the background, the studies has carried on the regional coverage constellation configuration optimization design and the coordination control strategy. From the view to enhance the availability of the backup satellite, the orbit of the backup satellite is choice and designed, and the design performance analysis models of the constellation spatial backup strategy are established, and then the constellation spatial backup strategy optimization design method is presented based on the satellite reliability and MTTR (Mean Time To Repair).Based on the basic structures of the regional navigation constellation, the basic requirements and constraints of the regional navigation constellation are considered, and the mathematical model of the constellation optimization design is established. Based on the optimization strategy of MIGA (Multi-Island Genetic Algorithm), the global optimization design of the regional navigation constellation under the multi-objectives and the multi-constraints is carried on, and some design results, which meet mission requirements, are obtained. In view of the expansion performance requirements of the regional navigation constellation, the expansion optimization design of the regional navigation constellation based on the basic configuration is carried on. Considering the mission characteristics of the regional navigation constellation, the configuration design for the regional navigation constellation based on the compenstation strategy for the perturbations is finished.The staged characteristics of the deployment of the navigation constellation are analyzed, and the basic structure of the staged deployment navigation constellation is designed, and the design objectives and constraints of the staged deployment navigation constellation are determined, and then the optimization design models of the staged deployment navigation constellation are established. Overall considering the performance constraints including the configuration long-term stability, the configuration control, the system reliability, the system expense, the deployment strategy and the spatial backup strategy and so on and the mission requirements of the navigation constellation for our country, and then it is carried on the multi-objective optimization design of the staged deployment navigation constellation based on the optimization strategy of the multi-objective evolution algorithm and the multi-objective decision making of the linear weighted sum method.更多还原