Spectral Light Curve Simulation for Parameter Estimation from Space Debris

Abstract

Characterisation of space debris has become a fundamental task to facilitate sustainable space operations. Ground-based surveillance provides the means to extract key attributes from spacecraft. However, signal inversion attempts are generally under-constrained, which is why an increase in measurement channels through multispectral observations is expected to benefit parameter estimation. The current approach to simulating space debris observation at the Institute of Technical Physics of the German Aerospace Centre (DLR) in Stuttgart relies on monochromatic images taken from the POV-Ray render engine to form light curve signals. Rendered scenes are generated based on the location of an observer by propagating a target’s orbit and rotation. This paper describes the simulation of spectral light curves through the extension of DLR’s Raxus Prime simulation environment. Light reflections are computed using the Mitsuba2 spectral render engine, while atmospheric attenuation is accounted for by the radiative transfer library libRadTran. A validation of the simulator was achieved using multispectral measurements, carried out at the Uhlandshöhe research observatory in Stuttgart. Measured and synthetic data were found to be in agreement based on an RMS error <1% of the total measured signal count. Further, simulated spectral products were used to determine a target’s surface material composition and rotation state and examine aspects of laser ranging to non-cooperative targets.