Colloquium: Sergi Lopez Jimenez (Space Flight)

24 januari 2020 09:30 - Locatie: Lecture Room C, Faculty of Aerospace Engineering, Kluyverweg 1, Delft

New techniques for uncertainty realism improvement in Surveillance and Tracking orbit determination processes

The future space environment is predicted to grow in number of both operational and inactive man-made objects and the era of constellations is expected to arrive during the following years, with many telecom companies launching constellations of up to 12000 satellites. This situation will inevitably lead to over-population of the most demanded orbits making its exploitation a challenge to the scientific community as well as spacecraft operators. 

Regular products within the field of Space Surveillance and Tracking (SST) and Space Traffic Management (STM), such as high-risk collisions, upcoming re-entries or fragmentations, rely both on the estimated state and associated uncertainty of detectable Resident Space Objects (RSOs). Orbit Determination (OD) algorithms provide the required estimations, assuming that the uncertainty in the state of the object is properly characterized by its state vector covariance and assuming Gaussian processes.

However, a common problem of OD processes is the misrepresentation of the RSOs uncertainty through the estimated and predicted covariance. Ultimately, this causes a great impact in the quality and accuracy of SST products as the covariance is overly optimistic (too small) and the true uncertainty of the object is not properly captured. The aim of this work is to devise a novel methodology to improve the covariance realism of OD and orbit propagation processes through the classical theory of consider parameters of batch least-squares estimators. 

The outcome of this project is a software application integrated as part of the GMV’s SST software suite that can deliver efficient and effective covariance realism improvement for a more accurate provision of SST products.