Abstract
AbstractThe growth of both operational satellites and orbital debris is creating the requirement for more robust Space Surveillance and Tracking (SST)-related applications. These systems necessarily must leverage ground-based sensors (optical and radar) to realise higher performance solutions. In this context, the European Union Space Surveillance and Tracking (EUSST) consortium groups European national agencies and institutions, and is in charge of carrying out the following services: conjunction analysis, fragmentation analysis and re-entry prediction, and the Italian Air Force is in charge of the latter two. In this framework, the Italian SST Operational Centre (ISOC) has recently upgraded its system to the ISOC Suite, an integrated platform providing multiple functions and services in the SST domain. This paper presents the orbit determination functions provided by the novel ISOC Suite. First, a statistical index is computed to assess the measurements correlation to a catalogued object. If it is successful, the object predicted orbit is refined through measurements according either to batch or sequential filters; otherwise these are used to refine a first estimate of the target orbital state computed according to dedicated methodologies. After the presentation of the prototypal software architecture, the ISOC Suite performance are assessed and discussed both in terms of synthetic and real data.
Publisher
Springer Science and Business Media LLC
Reference42 articles.
1. ESA’s Annual Space Environment Report. Technical report, European Space Agency, Space Debris Office (2022)
2. Flohrer, T., Krag, H.: Space surveillance and tracking in ESA’s SSA programme. In: 7th European conference on space Debris, vol. 7. (2017)
3. European Union Space Surveillance and Tracking Service Portfolio. Technical report, EUSST (2021)
4. Bonaccorsi, S., Montaruli, M.F., Di Lizia, P., Peroni, M., Panico, A., Rigamonti, M., Del Prete, F.: Conjunction analysis software Suite for space surveillance and tracking. Aerospace. 11, 122 (2024). https://doi.org/10.3390/aerospace11020122
5. De Vittori, A., Palermo, M.F., Di Lizia, P., Armellin, R.: Low-thrust collision avoidance maneuver optimization. J. Guid. Control Dyn. 45(10), 1815–1829 (2022). https://doi.org/10.2514/1.G006630
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