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One-Shot Initial Orbit Determination in Low-Earth Orbit
Due to the importance of satellites for society and the exponential increase in the number of objects in orbit, it is important to accurately determine the state (e. g., position and velocity) of these Resident Space Objects (RSOs) at any time and in a timely manner.
Predicting the Probability of Collision of a Satellite with Space Debris: A Bayesian Machine Learning Approach
Such a dense space environment increases the risk of collisions between space objects endangering the whole space population.
Finding Real-World Orbital Motion Laws from Data
The method offers the advantage of delivering interpretable, accurate, and complex models of orbital motion that can be employed for propagation or as inputs to predictive models for other variables of interest, such as atmospheric drag or the probability of collision in an encounter with a spacecraft or space objects.
Probability of Collision of satellites and space debris for short-term encounters: Rederivation and fast-to-compute upper and lower bounds
It is estimated that, in orbit, there are millions of fragments a few millimeters in size and thousands of inoperative satellites and discarded rocket stages.
Taxonomy for Resident Space Objects in LEO: A Deep Learning Approach
Our proposed taxonomy and model offer a significant contribution to the ongoing efforts to mitigate the overall risks posed by the increasing number of RSOs in orbit.
Statistical Learning of Conjunction Data Messages Through a Bayesian Non-Homogeneous Poisson Process
In fact, the rate at which the CDMs are issued depends on the behaviour of the objects as well as on the screening process performed by third parties.
Predicting the Position Uncertainty at the Time of Closest Approach with Diffusion Models
As a result, spacecraft collision avoidance procedures have become an essential part of satellite operations.
Conjunction Data Messages for Space Collision Behave as a Poisson Process
(2) When exactly and with what uncertainty will the next message arrive?
Conjunction Data Messages behave as a Poisson Process
(2) When exactly and with what uncertainty will the next message arrive?
