Jorge Rubio, GMV & Universidad Carlos III de Madrid; Adrian de Andrés, GMV; Carlos Paulete, GMV; Ángel Gallego, GMV; Jose Miguel Lozano, GMV; Diego Escobar, GMV; Alberto Agueda, GMV
Keywords: attitude estimation, attitude monitoring, light curve, three-axis stabilised satellite
Abstract:
Accurate knowledge of the attitude of Resident Space Objects (RSOs) has become essential for different space debris mitigation activities, including collision risk assessment and atmospheric re-entry prediction. Attitude monitoring is also highly relevant for routine space operations and for detecting potential anomalies in controlled satellites. This study focuses on monitoring the attitude of three-axis stabilised satellites with known geometries using light curves. The worst-case scenario is considered, in which no prior knowledge of the attitude is available, thereby providing a realistic representation of operational conditions in which a satellite has deviated from its nominal attitude control mode. Moreover, the optical properties of the materials constituting the satellite’s surfaces are assumed to be unknown, as their diversity makes them difficult to estimate. Even if the materials were well characterised, prolonged exposure to the space environment would likely cause ageing effects that unpredictably alter their optical properties.
In addition to the unknown optical properties, the proposed methodology is robust to uncertainties in aerosol optical depth (AOD), which models the extinction of light in the atmosphere due to aerosols. This parameter depends on highly variable factors such as atmospheric humidity and the concentration of dust or pollutants suspended in the air. Accurately determining the AOD a priori is challenging, as it would require precise meteorological measurements at the sensor location and time of observation. Consequently, the proposed methodology estimates the satellite attitude under conditions of unknown optical properties and AOD, a task complicated by the inherent ambiguity of the measurement, whereby multiple combinations of attitude, optical, and atmospheric parameters can result in similar light curves. To address this, the approach integrates statistical inference with optimisation and data analysis techniques to ensure accurate and robust estimation of the unknown parameters. Developed with operational applicability in mind, the methodology enables precise attitude estimation within minutes. Its performance is validated through a realistic test case, demonstrating its suitability for real-world operational scenarios.
Date of Conference: September 16-19, 2025
Track: Satellite Characterization