1 citations · 3 across the 9 of their papers we have counts for
5 papers · 1 filter
Predicting the Probability of Collision of a Satellite with Space Debris: A Bayesian Machine Learning Approach
João Simões Catulo, Cláudia Soares, Marta Guimarães
Space is becoming more crowded in Low Earth Orbit due to increased space activity. Such a dense space environment increases the risk of collisions between space objects endangering…
Finding Real-World Orbital Motion Laws from Data
João Funenga, Marta Guimarães, Henrique Costa +1
A novel approach is presented for discovering PDEs that govern the motion of satellites in space. The method is based on SINDy, a data-driven technique capable of identifying the u…
Taxonomy for Resident Space Objects in LEO: A Deep Learning Approach
Marta Guimarães, Cláudia Soares, Chiara Manfletti
The increasing number of RSOs has raised concerns about the risk of collisions and catastrophic incidents for all direct and indirect users of space. To mitigate this issue, it is…
Statistical Learning of Conjunction Data Messages Through a Bayesian Non-Homogeneous Poisson Process
Marta Guimarães, Cláudia Soares, Chiara Manfletti
Current approaches for collision avoidance and space traffic management face many challenges, mainly due to the continuous increase in the number of objects in orbit and the lack o…
Predicting the Position Uncertainty at the Time of Closest Approach with Diffusion Models
Marta Guimarães, Cláudia Soares, Chiara Manfletti
The risk of collision between resident space objects has significantly increased in recent years. As a result, spacecraft collision avoidance procedures have become an essential pa…