No abstract
<p>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.</p> <p>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.</p> <p>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.</p> <p>In this context, The <em>Generic Data Reduction Framework for Space Surveillance -&#160; <strong>gendared,</strong></em> 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. <strong><em>gendared</em></strong> 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.</p> <p>The key aspects that drove the development of <strong><em>gendared</em></strong> 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.</p> <p>As of the end of the prototyping phase and the acceptance of the software by ESA, <strong><em>gendared</em></strong> 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.</p> <p>Furthermore, since mid-2020, <strong><em>gendared</em></strong> is part of a larger architecture of GMV products supporting the operational data processing activities in Romanian Space Agency&#8217;s SST Operational Centre (COSST), which ensures the Romanian contribution to the EUSST Consortium. In this case <strong><em>gendared</em></strong> 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.</p> <p><br />Most recently GMV has also won a Romanian Research & Development grant to upgrade <strong><em>gendared</em></strong> 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 <strong><em>gendared </em></strong>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.</p> <p>&#160;</p> <p><img src="data:image/png;base64, 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