Space Oddity? A Statistical Formulation of Conjunction Assessment

TL;DR

This paper introduces a statistical model for satellite conjunction assessment, enabling more accurate inference on miss distances and highlighting limitations of traditional collision probability estimates.

Contribution

It presents a novel statistical formulation for conjunction analysis that improves inference accuracy and addresses biases in collision probability estimates.

Findings

Accurate inference on miss distance is achievable even with velocity uncertainty.

Traditional collision probability estimates can be significantly biased.

Monte Carlo simulations demonstrate the model's excellent performance.

Abstract

Satellite conjunctions involving "near misses" of space objects are becoming increasingly likely. One approach to risk analysis for them involves the computation of the collision probability, but this has been regarded as having some counter-intuitive properties and its interpretation has been debated. This paper formulates an approach to satellite conjunction based on a simple statistical model and discusses inference on the miss distance between the two objects, both when the relative velocity can be taken as known and when its uncertainty must be taken into account. It is pointed out that the usual collision probability estimate can be badly biased, but that highly accurate inference on the miss distance is possible. The ideas are illustrated with case studies and Monte Carlo results that show its excellent performance.