一种卫星对地观测任务完成概率的估计模型
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

国家部委资助项目


An enforceability probability estimation model for satellite observing tasks
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对及时响应用户提出的观测需求和高效实施卫星任务规划调度的需要,提出快速估计卫星对地观测任务完成可能性的现实问题,利用Logistic回归方法建立了一种卫星对地观测任务完成概率的估计模型。分析影响侦察任务完成概率的相关因素,包括侦察任务自身属性、资源约束、任务之间竞争关系等;从影响因素中提炼出刻画影响因素的模型变量,给出其量化方法,并初步构建了Logistic回归分析模型;基于卫星成像侦察任务规划系统开展实验,获取自变量与规划结果方面的样本数据;采用Logistic回归分析方法对样本数据进行分析,确定模型中的变量、参数及函数形式。结论表明,模型具有很好的统计特性。

    Abstract:

    The enforceability probability of satellite observation requires timely and accurate estimation to provide the fundamental basis for satellite task planning and scheduling. An estimation model of the enforceability probability of satellite earth observation is established based on the Logistic regression method. Firstly, the influence factors of observation enforceability probability were analyzed, including the property of observation task, resources limitation, competitive relations among tasks, etc. Secondly, independent variables were extracted and their quantitative methods were given, then the Logistic regression model was established. Thirdly, experiments were implemented on the planning and scheduling system of satellite imaging observation to obtain the sample data of independent variables and planning results. Moreover, the sample data was analyzed by using the Logistic regression method, and then the variables and parameters of the model and the function forms were all determined, Lastly, the effectiveness of the model was validated.

    参考文献
    相似文献
    引证文献
引用本文

李志猛,谈群,刘刚,等.一种卫星对地观测任务完成概率的估计模型[J].国防科技大学学报,2013,35(6):185-190.
LI Zhimeng, TAN Qun, LIU Gang, et al. An enforceability probability estimation model for satellite observing tasks[J]. Journal of National University of Defense Technology,2013,35(6):185-190.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2013-04-01
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2014-01-08
  • 出版日期:
文章二维码