中国空间科学技术

中国空间科学技术 ›› 2020, Vol. 40 ›› Issue (6): 33-40.doi: 10.16708/j.cnki.1000-758X.2020.0069

• 研究探讨 • 上一篇    下一篇

链路统计分析中导出参数概率计算方法研究

李赞，樊敏   

  1. 北京跟踪与通信技术研究所，北京100094
  • 出版日期:2020-12-25 发布日期:2020-11-25
  • 基金资助:
    载人航天领域预先研究项目（060301）

Study on probability calculation method of derived parameters in link statistical analysis

LI Zan，FAN Min   

  1. Beijing Institute of Tracking and Telecommunication Technology, Beijing100094, China
  • Published:2020-12-25 Online:2020-11-25

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摘要： 为了适应深空探测任务需求，有效利用测控资源，提高链路计算精度，对天地链路统计分析基本方法进行了研究，对CCSDS标准建议的3种链路参数的概率密度函数特性进行了系统分析，提出了一种当链路参数不满足李雅普诺夫（Lyapunov）条件时，利用鞍点逼近估计尾概率函数确定导出参数取值概率的方法。通过理论分析和实例计算表明，采用该方法得到的导出参数的概率分布特性与真实值基本一致，进一步完善了天地链路统计计算方法，使天地链路统计分析方法更具有普遍性。

关键词: 链路统计分析, 导出参数, 概率密度函数, 鞍点估计, 尾概率函数

Abstract: In order to meet the requirements of deep space exploration, effectively utilize the TTC resource, and improve the link calculation accuracy, statistical analysis method of the link was studied and the characteristics of probability density functions of three link parameters recommended by the Consultative Committee for Space Data System (CCSDS) were analyzed. A method was put forward when the link parameters can not meet the Lyapunov condition that uses the saddle point approximation to estimate the tail probability function to determine the derived parameter probabilities. The result shows that the parameters derived of this method are similar to that of the real function. This method can further improve the statistical calculation method of the link analysis and make it more universal.

Key words: link statistical analysis, derived parameter, probability density function, saddle point approximation, tail probability function