Abstract
The risk of collisions in Earth’s orbit is growing
markedly. In January 2021, SpaceX and OneWeb
released an operator-to-operator fact sheet that highlights
the critical reliance on conjunction data messages
(CDMs) and observations, demonstrating the need for a
diverse sensing environment for orbital objects. Recently,
the University of Oxford and the University of Surrey
developed, in collaboration with Trillium Technologies
and the European Space Operations Center, an opensource
Python package for modeling the spacecraft collision
avoidance process, called Kessler. Such tools
can be used for importing/exporting CDMs in their standard
format, modeling the current low-Earth orbit (LEO)
population and its short-term propagation from a given
catalog file, as well as modeling the evolution of conjunction
events based on the current population and observation
scenarios, hence emulating the CDMs generation
process of the Combined Space Operations Center
(CSpOC). The model also provides probabilistic
programming and ML tools to predict future collision
events and to perform Bayesian inference (i.e., optimal
use of all available observations).
In the framework of a United Kingdom Space Agency-funded
project, we analyze and study the impact of megaconstellations
and observation models in the collision
avoidance process. First, we monitor and report how the
estimated collision risk and other quantities at the time of
closest approach (e.g. miss distance, uncertainties, etc.)
vary, according to different observation models, which
emulate different radar observation accuracy. Then, we
analyze the impact of future megaconstellations on the
number of warnings generated from the increase in the
number of conjunctions leading to an increased burden on
space operators. FCC licenses were used to identify credible
megaconstellation sources to understand how a potential
consistent increase in active satellites will impact
LEO situational safety. We finally present how our simulations
help understand the impact of these future megaconstellations
on the current population, and how we can
devise better ground observation strategies to quantify future
observation needs and reduce the burden on operators.