The Research Project
In recent years, several comprehensive catalogues for relational space debris information have been developed and put into operation. These databases contain millions of entries, providing vital metadata such as orbital parameters, object size, and satellite origin and many more. For the design and execution of future satellite missions, this information is indispensable for identifying and maintaining safe orbits. However, the sheer volume of data presents a significant challenge: simple 3D renderings of planned trajectories amidst a cloud of debris do not provide sufficient actionable insights for mission planners
The Research Questions
This thesis investigates how to transform raw orbital data of the spacecraft and debris into meaningful visualizations that directly inform end-users when and where a mission profile might become critical. A key focus is the representation of uncertainty - specifically the risk of secondary debris generation from potential collisions. The research should explore whether volume-based visualization on spatial density offers a more intuitive understanding of high-risk zones compared to individual trajectory plotting. Furthermore, the study identifies the interaction patterns, such as spatio-temporal filtering and linked 2D-3D views, required for effective orbital exploration.
Your Qualification
- You are studying in Computer Science, Mathematics, Data Science, or similar courses
- You own good knowledge in programming, preferably in C++
- Furthermore, you have interest in high-quality software development
- Ideally you also have basic knowledge of computer graphics and know the topic of visual analytics
- And you are a team player with creativity, independence and personal responsibility
Wir freuen uns darauf, dich kennenzulernen!
Fragen zu dieser Position (Kennziffer 5119) beantwortet dir gerne:
Prof. Dr. Andreas Gerndt
Tel.: +49 531 295 2782