Tristan Meyer, German Aerospace Center (DLR); Denise Keil, German Aerospace Center (DLR); Daniel Traub, German Aerospace Center (DLR); Stefan Scharring, German Aerospace Center (DLR); Wolfgang Riede, German Aerospace Center (DLR); Thomas Dekorsy, German Aerospace Center (DLR); Max Nussbaum, DiGOS Potsdam GmbH; Michael Lengowski, University of Stuttgart; Robin Schweigert, University of Stuttgart; Sabine Klinkner, University of Stuttgart
Keywords: Light curves, object characterization, light curve simulation, reflectivity maps, SSA, space debris, Flying Laptop
Abstract:
Nowadays, the Low Earth Orbit is crowded. A high number of active satellite missions, about 900.000 mostly undetected but critical space debris objects, dead satellites and expended rocket stages are creating a pressing need to improve space situational awareness. The shape, composition, and attitude of debris objects are largely unknown, with rotational behavior playing a crucial role for in-orbit missions which aim to grasp space objects. In-orbit missions can facilitate the maintenance or repair of inactive satellites, as well as their removal. The latter could apply also for spent rocket bodies, mission-related objects or debris fragments, thereby fostering a sustainable utilization of the space environment. To achieve this, understanding the rotational behavior or attitude evolution prior to the mission is essential. Dynamic object information can be obtained through ground-based measurements by the acquisition and analysis of light curves from observations of sunlight which is reflected from the debris. Subsequently, for an in-depth characterization of the object’s rotational state, these measurements are correlated with simulated data.
In this study we validate our light curve simulation using the Flying Laptop satellite, COSPAR-ID 2017-042G, which was developed and is operated by the University of Stuttgart’s Institute of Space Systems (IRS). The satellite orbits at a relatively low altitude of 600 km and is operational. Thus, it can easily be used as an orbital object for light curve assessment and attitude analysis. The simulated data is supported by laboratory measurements of the outer surface materials, encompassing the spectral reflectance and surface roughness. Both sets of data will be used as input for the generation of bidirectional reflectance distribution functions (BRDFs) of the materials, which, in turn, serve as input to our software tool Raxus Prime. It enables spectrally resolved simulations of the object’s brightness, utilizing a physics-based rendering engine. The tool incorporates a facet model, where each facet is assigned the BRDF of the corresponding material, spectrally resolved atmospheric transmission, and instrument parameters. Consequently, high-fidelity simulations of the object’s on-ground intensities can be produced at each attitude, which serves as a starting point for the comparison of real-life telescopic measurement data of the Flying Laptop satellite, i.e., light curves, with the light curves from the simulations.
A powerful tool in further characterizing catalogued objects are reflectivity maps that project the reflected sunlight intensity of the object via the phase vector into a body-fixed frame. Due to the unique composition, shape, and dimensions of each object, these maps are distinct for every individual object, which is illustrated with the Flying Laptop satellite as a target sample. If the geometric configuration and reflective characteristics of the target’s external structure are established, simulations of these maps can be conducted for all potential phase vector orientations within the body-fixed frame. Measured light curves can then be matched with the simulated maps to extract the best-fitting attitude evolution and, consequently, the rotational behavior. The advantage of reflectivity maps lies in the fact that they only need to be generated once per object, which reduces the computational effort for light curve analysis. Furthermore, projecting measured light curves on the maps provides information about which intensities, resulting from the corresponding attitude, are covered for certain overflights. This enables the identification of unseen parts of the map and, consequently, attitudes not yet observed, which is valuable when characterizing the dynamics like precession and nutation of the object. Validating the accuracy and technique of reflectivity maps enables the potential utilization for fast attitude assessment via light curves for objects with known geometry and composition, paving the way for light curve inversion, e.g., for attitude determination of individual passes.
Date of Conference: September 17-20, 2024
Track: Satellite Characterization