Volume 31 Issue 4
Jul.  2011
Turn off MathJax
Article Contents
Yang Xu, Liu Jing, Wang Ronglan, Yu Youcheng. Collision prediction analysis using refined error data[J]. Chinese Journal of Space Science, 2011, 31(4): 520-526. doi: 10.11728/cjss2011.04.520
Citation: Yang Xu, Liu Jing, Wang Ronglan, Yu Youcheng. Collision prediction analysis using refined error data[J]. Chinese Journal of Space Science, 2011, 31(4): 520-526. doi: 10.11728/cjss2011.04.520

Collision prediction analysis using refined error data

doi: 10.11728/cjss2011.04.520 cstr: 32142.14.cjss2011.04.520
More Information
  • Corresponding author: Yang Xu
  • Received Date: 1900-01-01
  • Rev Recd Date: 1900-01-01
  • Publish Date: 2011-07-15
  • With the expansion of human's activity in the outer space, the population of the space debris has grown greatly. Several collisions and breakup events in the recent period increased the total number of space debris sharply. These debris are causing serious threat to orbital spacecraft, and efficient protection must be done to deal with the growing collision risk. Space debris collision avoidance job mainly aims at big space debris that can be monitored, and predicting the collision risk between spacecraft and space debris and then evaluating the risk through certain collision criterion. So a reasonable orbit maneuver decision can be made to perform any necessary mitigate action to avoid possible collisions. Collision probability is the primary index to evaluate collision risk. The combined object size, the minimum distance and errors are main factors affecting collision probability. When the combined object size and the minimum distances are not different significantly, error data will be the crucial factor affecting collision probability. This paper brings forward a method of using refined error data to compute collision probability on the basis of whole day errors. And this method makes improvement in analyzing possible collisions.

     

  • loading
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article Views(3047) PDF Downloads(1082) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return