Collision probability of space objects

Abstract

The primary objective of this research project was to conduct a comprehensive analysis of stateof- the-art algorithms designed for the calculation of Collision Probability between satellites and other space objects, particularly space debris. Our investigation revealed a categorization of space object encounters into three main types: instantaneous, short-term, and long-term encounters. Notably, we identified that collision probability assessment for each encounter type could be further subcategorized as cumulative and instantaneous. To evaluate the accuracy of collision probability calculations, we focused on short-term encounters and implemented two widely utilized methods: Patera’s method and Alfano’s method. These methods were rigorously tested against a reference collision probability derived through the Monte Carlo Approach. Our findings shed light on the effectiveness and precision of these methodologies in predicting collision probabilities for short-term space object encounters. In conclusion, this research contributes valuable insights into the categorization of space object encounters and the efficacy of specific algorithms in predicting collision probabilities. The comparative analysis of Patera’s and Alfano’s methods provides a nuanced understanding of their performance against a benchmark Monte Carlo Approach, offering implications for the enhancement of collision probability calculations in space debris management.