Europlanet Science Congress 2022
Palacio de Congresos de Granada, Spain
18 – 23 September 2022
Europlanet Science Congress 2022
Palacio de Congresos de Granada, Spain
18 September – 23 September 2022
EPSC Abstracts
Vol. 16, EPSC2022-35, 2022, updated on 06 Jul 2022
Europlanet Science Congress 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

gendared: the Generic Data Reduction Framework for Space Surveillance

Ana-Maria Piso-Grigore1, Angelo Voicu1, Pierre Sprimont1, Bogdan Bija2, Oscar Alonso-Lasheras3, and Vlad Olteanu1
Ana-Maria Piso-Grigore et al.
  • 1GMV Innovating Solutions, 246C Calea Floreasca, Sector 1, 011476 Bucharest, Romania
  • 2GMV NSL, HQ Building, Thomson Avenue, Harwell Campus, OX11 0GD , Oxfordshire, UK
  • 3GMV Aerospace and Defence S.A.U., Santiago Grisolía, 4, PTM Tres Cantos, 28760 Madrid, España

Space Surveillance and Tracking (SST) requires the development of observational campaigns to early identify Earth orbiting objects, estimate their orbital elements and monitor the evolution of their trajectories.

With a growing number of satellites being launched every year, there is an increasing interest in SST at worldwide level and especially across the EU. In this context, Romania is one of the few EU member states involved in such activities.

SST systems must implement an Image Data Reduction Subsystem, able to timely process the continuous exposures taken in an automatic and continuous way by optical telescopes, analyse these data sets to identify objects of interest (target objects) and retrieve accurate measurements of the apparent position and brightness of the detected objects. In the last step, the tool generates tracklet information for the identified target objects.

In this context, The Generic Data Reduction Framework for Space Surveillance -  gendared, prototyped initially by GMV in the frame of an ESA Romanian Industry Incentive Scheme project, is intended to be used in order to support the operational reduction of the image data acquired by optical telescopes. gendared receives as input the raw images taken by the telescope, and generates as output astrometric and photometric data for the target objects detected in the observation images.

The key aspects that drove the development of gendared and its advantages include the fact that the software is autonomous and unassisted, can process images in near real-time, can cope with different image acquisition schemas, and is configurable and modular.

As of the end of the prototyping phase and the acceptance of the software by ESA, gendared has been successfully tested and validated on Romanian telescopes and developed further for various operational use cases of different telescopes, such as the German Aerospace Centre (DLR) telescopes.

Furthermore, since mid-2020, gendared is part of a larger architecture of GMV products supporting the operational data processing activities in Romanian Space Agency’s SST Operational Centre (COSST), which ensures the Romanian contribution to the EUSST Consortium. In this case gendared is covering, in a centralized architecture, the processing of the data coming from the Romanian optical telescopes involved in EUSST. The software was further upgraded for this purpose, with new algorithms and processing pipelines included.

Most recently GMV has also won a Romanian Research & Development grant to upgrade gendared with artificial intelligence algorithms. This project involves a consortium led by GMV, with the Faculty of Automatic Control and Computer Science and the Astronomical Institute of the Romanian Academy as partners. By integrating artificial intelligence techniques into the current gendared framework, we aim to improve its performance, reduce user involvement and computational costs, as well as increase pipeline autonomy. The upgraded solution will be tested and validated in representative scenarios based on real telescope data, with the ultimate goal of converting the prototype into a product that will be validated in an SST operational environment on a wide range of telescopes.



How to cite: Piso-Grigore, A.-M., Voicu, A., Sprimont, P., Bija, B., Alonso-Lasheras, O., and Olteanu, V.: gendared: the Generic Data Reduction Framework for Space Surveillance, Europlanet Science Congress 2022, Granada, Spain, 18–23 Sep 2022, EPSC2022-35,, 2022.


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