Abstract:
This paper documents the findings of a demonstration of the benefits of multi-source data fusion and advanced analytics to achieving accurate Space Situational Awareness (SSA) for the Space Traffic Coordination and Management (STCM) mission. After extensive testing and statistical assessments of predictive positional accuracy for seventeen spacecraft spanning LEO, MEO and GEO orbit regimes, the team found that fusing government, commercial, and satellite operator data with advanced data processing techniques results is essential to enabling comprehensive, timely, and accurate collision avoidance services for all satellite operators.
In this assessment of spacecraft positional accuracy, which was conducted between 15 and 30 September 2020, the team was able to “crowd source” data from SSA data providers (e.g., radar or optical sensor information), government and satellite operators to typically improve SSA accuracy by ten to fifty percent in LEO and a factor of ten or more in GEO, thereby dramatically improving flight safety.
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Oltrogge, D.L., Wauthier, P., Vallado, D.V., Alfano, S., and Kelso, T.S., “Results Of Comprehensive STCM Data Fusion Experiment,” Proc. 8th European Conference on Space Debris (virtual), Darmstadt, Germany, 20-23 April 2021, https://conference.sdo.esoc.esa.int/proceedings/sdc8/paper/263/SDC8-paper263.pdf (accessed 30 September 2021).
