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• 空间探测技术 • Previous Articles     Next Articles

Collision prediction analysis using refined error data

Yang Xu, Liu Jing, Wang Ronglan, Yu Youcheng   

  1. (National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012; Center for Space Science and Applied Research, Chinese Academy of Sciences, Beijing 100190)
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-07-15 Published:2011-07-15
  • Contact: Yang Xu

Abstract: 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.

Key words: AR5395, Evoluation, Periodicity