Autonomous Detection of Satellite Orbital Anomalies Through Statistical Behavioural Analysis
Pietro RUSSO, Giorgio ISOLETTA, Roberto OPROMOLLA, Giancarmine FASANO
Abstract. The proliferation of Resident Space Objects (RSOs) within the near-Earth orbital regime presents serious challenges for the sustainability and safety of space operations. Accurate tracking and cataloguing of RSOs are critical for Space Situational Awareness (SSA) and Space Traffic Management (STM). These tasks are hindered by unknown maneuvers of active satellites, which can lead to difficulties in correlating new observations with existing catalogued data. To address this issue, the study proposes a novel algorithm to detect satellite orbital anomalies based on a statistical analysis of its operational behaviour. Specifically, the algorithm is designed to detect anomalous or non-nominal satellite activities through the comparison of its most recent Pattern of Life with its current behaviour. The integration of statistical behavioural models into SSA pipelines provides a scalable solution for maintaining catalogue integrity in the increasingly congested orbital environment, by identifying satellite orbital anomalies.
Keywords
Anomaly Detection, Maneuver Detection, Pattern of Life, Space Situational Awareness, Space Surveillance & Tracking
Published online 7/20/2026, 6 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Pietro RUSSO, Giorgio ISOLETTA, Roberto OPROMOLLA, Giancarmine FASANO, Autonomous Detection of Satellite Orbital Anomalies Through Statistical Behavioural Analysis, Materials Research Proceedings, Vol. 69, pp 936-941, 2026
DOI: https://doi.org/10.21741/9781644904251-165
The article was published as article 165 of the book CEAS – AIDAA Conference 2025
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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