Postgraduate research project

Data-driven Density Modelling (D3M) through machine learning for satellite orbit prediction

Funding
Fully funded (UK only)
Type of degree
Doctor of Philosophy
Entry requirements
First-class Masters degree View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date

About the project

This project will use machine learning and big data techniques to develop real-time satellite orbit predictions for safer, smarter space traffic management. It aims to integrate high-precision laser ranging satellite tracking data to continuously update the biggest unknown, atmospheric density. This can improve tracking accuracy by up to an order of magnitude.

The rise of satellite mega-constellations and improved tracking systems has led to an explosion of precise satellite data. This project offers the chance to help solve one of the biggest challenges in modern space operations: managing an increasingly congested low Earth orbit (LEO) environment.

Working with leading academics and our industry partner Lumi Space)