Background:

At GMV, you will join a unique, team-oriented environment where talent, creativity, and commitment are continuously encouraged and challenged. You will become part of an international, multidisciplinary team of more than 100 engineers working on Space Surveillance and Tracking (SST) and Space Traffic Management (STM), contributing directly to space sustainability while boosting your career.

The rapid increase in manoeuvring spacecraft has made the maintenance of space catalogues increasingly complex. Custody breaks, i.e., when manoeuvres are unannounced or dynamics are uncertain, pose significant risks, especially under sparse or noisy observations. Developing robust orbit determination methods is key to preserving catalogue integrity and ensuring the safety of future space operations.

Tasks:

The goal of this thesis is to explore and advance tracking techniques for objects in an uncertain dynamical environment. You will have the opportunity to:

• Studying space object catalogue maintenance and orbit determination theory.
• Analysing orbit determination cases in challenging conditions with both simulated and real observations.
• Comparing and assessing estimation strategies, such as filtering, smoothing, and uncertainty inflation.
• Developing a prototype algorithmic framework, laying the groundwork for future operational use.

Requirements / Skills:

• Enrolment in a Master’s program in Computer Science, Computational Engineering, Mechatronics, Mechanical Engineering, Aerospace Engineering, or a related field.
• Strong programming skills in Python (required); proficiency in C++ is a plus.
• Solid knowledge of astrodynamics (required).
• Background in statistical inference and dynamical systems (beneficial).
• Previous exposure to the lectures “Space Flight Mechanics” and “Space Debris – Risks, Surveillance and Mitigation” is an advantage.

Organisational:

• Start November
• Working student salary