Forecasting air drag with deep learning helps predict when uncontrolled satellites and rocket stages fall to Earth
Researchers are using deep learning and orbital mechanics to improve predictions for when uncontrolled space debris will re-enter Earth's atmosphere. The study aims to mitigate risks associated with the growing number of defunct satellites and rocket stages in orbit.
Why it matters
As the volume of space debris increases, accurate re-entry forecasting is critical for public safety and global space traffic management.
edited by Lisa Lock , reviewed by Robert Egan
This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in