Giuseppe Crescenzio, Officina Stellare SpA; Richard Tozzi, Officina Stellare SpA; Mirco Bartolomei, Officina Stellare SpA; Simone Caretta, Officina Stellare SpA; Andrea Turella, Officina Stellare SpA; Carmelo Arcidiacono, INAF-Osservatorio Astronomico di Padova; Simone Zaggia, INAF-Osservatorio Astronomico di Padova; Matteo Simioni, INAF-Osservatorio Astronomico di Padova; Luca Cortese, Università degli Studi di Padova; Miriana Lucchini, Università degli Studi di Padova
https://doi.org/10.64861/QQHJ3465
Keywords: SSA, GEO satellites, polarimetry, Wollaston prism, AFOSC, non-resolved characterization.
Abstract:
Space Situational Awareness (SSA) in GEO orbit relies on unresolved optical signatures. While photometry is widely used, polarimetry offers additional discriminants linked to surface materials and attitude._x000D_
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We present results from an experimental campaign aimed at characterizing GEO satellites through polarimetric measurements. Observations were conducted at the Copernico telescope (INAF, Cima Ekar), operating at the Cassegrain focus and equipped with AFOSC, which integrates a double Wollaston prism in pupil division for simultaneous acquisition of orthogonal polarization states._x000D_
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The dataset spans multiple nights and seasonal conditions, covering a range of solar phase angles. Data reduction includes normalization by phase angle and comparison with simulated signatures based on panel orientation and bus geometry. A key focus is to investigate possible seasonal effects on polarization curves and separate them from attitude-related variations. In addition, multispectral polarimetric measurements provide insights into satellite surface materials, offering an extra dimension for classification._x000D_
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This study demonstrates the feasibility of using polarimetric fingerprints for GEO satellite recognition and provides preliminary indications on the influence of geometry beyond phase angle alone. The approach sets the stage for integrating polarimetric observables into SSA pipelines and for developing predictive models of polarization signatures under varying orbital and seasonal conditions._x000D_
Date of Conference: September 15-18, 2026
Track: Satellite Characterization