摘要
导航星座的设计涉及诸多优化变量的选取,优化设计的目的是选取合适的优化变量使导航星座最大程度地满足人们需求。提出了将导航性能和卫星生产成本作为目标对导航星座进行多目标优化设计的研究方案,导航星座基本构型为中轨道(MEO)与地球静止轨道(GEO)卫星组成的混合星座,MEO卫星用于全球导航,GEO卫星用于增强星座对中国及周边地区的导航性能。探讨了MEO和GEO的轨道设计思路。阐述了星座导航性能与卫星生产成本的计算方法,并选取定位精度因子(PDOP)作为导航性能指标。介绍了基本粒子群算法和多目标优化的概念,提出了改进的多目标粒子群算法(MOPSO),给出了该算法的计算步骤和测试结果。讨论了导航星座多目标优化设计的数学模型,列举了优化设计变量的定义域,采用MOPSO算法对导航星座进行了多目标优化设计,通过分析优化设计结果,说明了导航星座多目标优化设计方案的可行性。
Navigation satellite constellation design involves the selection of many variables for optimization, the purpose of which is to search a set of variables and generate a constellation to satisfy human requirements to the maximum. In this acticle, a scheme that took navigation performance and satellite cost as objectives is pro- posed to optimize a eonstellation. The configuration of the constellation is a hybrid composed of medium-earth orbit （MEO） and geostationary orbit （GEO） satellites. MEO satellites are used for global navigation, while GEO yields the navigation strengthening over China and the neighboring regions. The method of designing MEO and GEO is expounded. The approaches to calculate navigation performance and satellite cost are analyzed, and position dilution of precision （PDOP） is selected as the guideline of navigation performance. The concept of basic particle swarm algorithm and multi-objective optimization is introduced, and a modified multiobjective particle swarm algorithm （MOPSO） is proposed. The calculation process and test results of MOPSO are given. The mathematic model of multi-objective optimization of navigation constellation is discussed, and the definition domain of design variables is listed. By analyzing the optimization results of a navigation constellation, it can be shown that the analysis method and design scheme are feasible.
出处
《航空学报》
EI
CAS
CSCD
北大核心
2009年第7期1284-1291,共8页
Acta Aeronautica et Astronautica Sinica
关键词
导航
星座
优化
多目标
粒子群算法
navigation
constellation
optimization
multi-objective
particle swarm algorithm
