Speaker
Description
Spacecraft attitude determination from passive optical observations remains a challenging inverse problem, particularly for resident space objects lacking cooperative sensors or telemetry. This work presents a methodology for reconstructing rotational state information from multi-colour photometric light curves by combining physically based brightness modelling, spectral reflectance effects, and statistical inversion techniques. The approach exploits time-varying brightness measurements acquired in multiple spectral bands to estimate rotational parameters such as spin period and spin-axis orientation while preserving consistency with observation geometry and illumination conditions. A dedicated simulation framework is used to generate synthetic multi-band light curves for controlled validation, enabling quantitative assessment of reconstruction performance under representative observing scenarios. Results demonstrate that multi-colour photometry provides additional constraints beyond monochromatic observations and can improve the observability and interpretability of attitude-related signatures. The presented framework establishes a reproducible foundation for photometric attitude reconstruction and highlights the potential of multi-band optical measurements for future space surveillance and space domain awareness applications.