Conjunction Data Messages for Space Collision Behave as a Poisson Process

Francisco Caldas, Cláudia Soares, Cláudia Nunes, Marta Guimarães
3/27/2023
stat.MLcs.LG

No confident code implementation found for this paper.

Abstract

Space debris is a major problem in space exploration. International bodies continuously monitor a large database of orbiting objects and emit warnings in the form of conjunction data messages. An important question for satellite operators is to estimate when fresh information will arrive so that they can react timely but sparingly with satellite maneuvers. We propose a statistical learning model of the message arrival process, allowing us to answer two important questions: (1) Will there be any new message in the next specified time interval? (2) When exactly and with what uncertainty will the next message arrive? The average prediction error for question (2) of our Bayesian Poisson process model is smaller than the baseline in more than 4 hours in a test set of 50k close encounter events.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Statistical Learning of Conjunction Data Messages Through a Bayesian Non-Homogeneous Poisson Process

91% match2023

Predicting the Probability of Collision of a Satellite with Space Debris: A Bayesian Machine Learning Approach

82% match2023

Probability of Collision of satellites and space debris for short-term encounters: Rederivation and fast-to-compute upper and lower bounds

77% match2023

Satellite Connectivity Prediction for Fast-Moving Platforms

73% match2025

A Machine Learning Approach to Predicting Single Event Upsets

73% match2023

Adaptive Active Learning for Online Reliability Prediction of Satellite Electronics

73% match2026

Cite this paper

@article{caldas2023conjunction,
  title  = {Conjunction Data Messages for Space Collision Behave as a Poisson Process},
  author = {Francisco Caldas and Cláudia Soares and Cláudia Nunes and Marta Guimarães},
  year   = {2023},
  eprint = {2303.15074},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.15074v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2303.15074.svg)](https://codeofpaper.com/paper/2303.15074)

Discussion