Mridul Songara, Digantara; Rithwik Neelakantan, Digantara; Latha Sridhar, Digantara; Sivalinga Raja Shanmugam, Digantara; Tanveer Ahmed, Digantara; Anirudh Sharma, Digantara
Keywords: Pattern of Life, Maneuver Pattern Violation, Residence Orbit Clustering, Maneuver Quantification
Abstract:
A new approach for detecting anomalous behaviors of Resident Space Objects (RSOs) through the analysis of historical orbital patterns is presented. In the increasingly congested and contested space domain, the ability to characterize the deviations from established Pattern of Life (PoL) behavior has become critical for enhancing Space Domain Awareness (SDA). Identifying deviations from normal orbital behavior shall assist in analyzing the intent and denies the first-mover advantage to the adversary. The solution approaches, as suggested in the literature, ranging from traditional statistics-based methods to sophisticated Artificial Intelligence methods to identify anomalous behaviors face a variety of challenges including scalability, generalization, explain-ability, speed, and integration with multi-modal data types. A hybrid approach is proposed to address some of these challenges. The proposed framework utilizes the publicly available data sources including historical Two-Line Elements (TLE) sets from Space-Track.org. The orbital data of RSOs, gathered over a duration in the past, is clustered using a densitybased method to characterize the orbital residence pattern of the RSO. Features extracted from historical data are further used to assign a distance-based metric to each maneuver conducted by the RSO. The method has been validated using known maneuver pattern violations – including the flagged PoL violation of COSMOS 2576 (NORAD ID 59773) maneuvers in February 2025. Evaluation with the proposed methodology showed different orbital clusters of the satellite, as well as the maneuvers which violated their historical pattern – identified as those falling outside the region of 95% confidence in the distribution of the historical maneuvers.
Date of Conference: September 16-19, 2025
Track: Satellite Characterization