Hyperspectral lightcurve inversion for attitude determination

Research output: Contribution to conferencePaper


Spectral lightcurves consisting of time series single-pixel spectral measurements of spacecraft are used to infer the spacecraft's attitude and rotation. Two methods are used. One based on numerical optimisation of a regularised least squares cost function, and another based on machine learning with a neural network model. The aim is to work with minimal information, thus no prior is available on the attitude nor on the inertia tensor. The theoretical and practical aspects of this task are investigated, and the methodology is tested on synthetic data. Results are shown based on synthetic data.
Original languageEnglish
Publication statusPublished - 4 Jan 2024
EventSciTech Forum 2024 - Orlando, FL, United States
Duration: 8 Jan 202412 Jan 2024


ConferenceSciTech Forum 2024
Country/TerritoryUnited States
CityOrlando, FL


  • hyperspectral data analysis
  • machine learning
  • neural networks
  • attitude determination and control systems


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