Henri Tarrieu, Aldoria; Lea Duthil, Aldoria; Sacha Redel, Aldoria; Alexis Petit, Aldoria
Keywords: Space Situational Awareness, Active Debris Removal, Photometry, Satellite Attitude Restitution, Optical Ground Sensors, Light Curve Inversion, Space Object Characterization
Abstract:
The current orbital congestion of Low Earth Orbit (LEO) region and the Geostationnary belt has become an increasingly worrying topic amongst all stakeholders of the space community, as we have seen the number of satellite launches skyrocket in the past decade. Although some of the lower altitude debris may decay in the Earth’s atmosphere on their own in short timespans, other objects like rocket bodies or defunct satellites pose a long-term threat to the health of active spacecraft and the environment. In this context, passive monitoring is not sufficient to ensure orbital safety. Some of the most promising solutions to this issue include Active Debris Removal (ADR), which is a challenging task as it requires a precise assessment of the uncontrolled target’s attitude behaviour during mission design.
Attitude assessment of such uncooperative objects can be performed using photometric data from optical ground sensors, as variations of the magnitudes of Resident Space Objects (RSO) can be observed during the visible passes. The technological advances regarding ground sensors for Space Situational Awareness (SSA) purposes, both on hardware and software levels, have increased the quality, quantity and availability of photometric data of RSO. This jump in measurement acquisition capacities allows us to develop and qualify a precise light reflection model for space objects. Our proposed method is based on a three-dimensional model of the target, enabling us to simulate the object’s photometric signature for any given tumbling motion and time. When optimized against photometric measurements, this model can help us perform light curve inversion, in order to extract the most likely tumbling rate and rotation axis state of the uncontrolled target. One of the major stakes of light curve inversion is the ability to reduce the parameter space of the problem, thus simplifying the photometric model based on the object physical characteristics. Without such work, the number and inter-correlatedness of variables makes the restitution of the most probable attitude solution a complex endeavor, often resulting in high uncertainty on the result. Combined with an unstable data quality due to varying environmental factors, it becomes necessary, at the very least, to know the influence of the different input parameters upon the restitution of the tumbling motion.
This paper proposes to investigate the impact of a few parameters on the attitude restitution, delving into the limitations of light curve analysis using such methods. We will thus focus on the sensitivity of our photometric model to variations of the tumbling motion itself and different object shapes. Starting with an assessment of the multi-modality of the problem caused by geometric properties, we will evaluate the efficiency of our light curve inversion algorithm through various case studies. The validity of the simulations presented for the case studies will be verified against real photometric data, ensuring the model is accurate. Considering and contrasting the results of this study, the paper concludes with potential reductions of the inversion problem, along with a presentation of the limitations of this attitude determination method and an opening on potential optimisation improvements.
Date of Conference: September 17-20, 2024
Track: Satellite Characterization