中国空间科学技术

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基于Bayes统计模型的卫星融合定轨方法研究

王炯琦;周海银;赵德勇;吴翊;   

  1. 国防科学技术大学数学与系统科学系,国防科学技术大学数学与系统科学系,国防科学技术大学信息系统与管理学院,国防科学技术大学数学与系统科学系 长沙410073,长沙410073,长沙410073,长沙410073
  • 发布日期:2008-06-25

Research on Fusion Method for Satellite Orbit Determination Based on Bayes Statistics Model

Wang Jiongqi1 Zhou Haiyin1 Zhao Deyong2 Wu Yi1 (1 Department of Mathematics and System Science,National University of Defense Technology,Changsha 410073) (2 School of Information System and Management,National University of Defense Technology,Changsha 410073)   

  • Online:2008-06-25
  • Supported by:
    国家自然科学基金(No.60572136);; 航天支撑技术基金项目(No.GFKD-HT-2006)

摘要: 根据目前天基导航系统现状,结合中国对低、中轨卫星精密定轨的要求,给出了天地基信息融合定轨的原理;结合卫星待估融合参数的先验信息,提出了基于Bayes统计模型的卫星精密定轨方法;在卫星观测的线性化融合模型中引入观测噪声,利用概率估计融合模型,根据Bayes理论进行卫星状态改进量的最大后验估计,并分析了Bayes估计方法的定轨精度;依据期望融合的待估改进量方差最小规则建立了相应的参数求解算法;最后以导航融合测控系统中测距和测速数据的融合定轨为例进行了仿真实验,表明该融合方法能够得到很好的定轨效果。

关键词: 信息融合, 贝叶斯定理, 统计模型, 先验估计, 精度分析, 轨道控制, 卫星

Abstract: According to the existing conditions of space-based navigating and positioning system and the precision orbit requirements of our country for LEO and MEO,the orbit determination principle based on information fusion was addressed. By introducing the prior information of satellite state parameters to be estimated,a method of information fusion for satellite orbit determination based on Bayes statistics model was presented,which added the observation noises into the linearized fusion model of observation equations,and then used the probability estimation fusion model to obtain the MAP(maximum aposteriori probability) of satellite states by Bayes theory,moreover,the orbit determination precision was analyzed.In addition,the fusion coefficients of multi-information were given based on the minimization of variance of desired fusion satellite states.Finally,through the simulation calculations and analysis for the distance data and velocity data integrative fusion strategy used for orbit determination based on combined measurement and control system,it indicates that this fusion method is more feasible and efficient.