Hyperspectral optical modeling of resident space objects at high spatial resolution

Abstract

The proliferation of objects in space is a growing concern, and it is becoming crucial to have reliable information about these objects in order to be able to locate and identify them. The aim of this paper is to present SIRIUS (Simulateur tool dedicated to optical modeling of resident space objects (RSO) in order to design or configure ground-based or space-based future observation systems. This tool presents an innovative feature as it generates hyperspectral highly spatially resolved images, at low computation time. Images are physically realistic thanks to the use of a global illumination method implemented through optimized rendering methods on GPU. The optical signature of a RSO is calculated in the visible range, with a possible extension to infrared. The radiative environment consists of the Sun and the Earth (ground, and possibly atmosphere and clouds), and the reflectivity of the RSO is described by Spectral Bidirectional Reflectance Distribution Function (sBRDF) for each material with physical modelling of geometry wrinkling for MLI materials. The orbit, orientation and mobile parts rotation (solar panels of satellite) are taken into account dynamically over time. The result of the simulation consists of a series of spectral images at the sensor of turbulence and the sensor may be modeled using a Point Spread Function (PSF). In this paper, we propose a validation of the SIRIUS tool based on a comparison of a simulated light curve obtained from ENVISAT images taken with the MeO telescope at the OCA (Côte d'Azur Observatory, France) during 2019, and an evaluation of the MLI wrinkling on the signature. The comparison between the simulated and experimental data of this uncontrolled satellite highlights the performance of this new predictive tool.