Space Debris Orbit and Attitude Prediction for Enhanced and Efficient Space Situational Awareness
Developing accurate models to predict the behavior of manmade debris in space could be the key to preventing collisions with satellites.
This research deals with the problem of modelling the orbit and attitude motion of uncontrolled manmade objects in orbit about the Earth, which tumble due to the natural influences of the near-Earth space environment. A mathematical, physics-based and computational approach is taken to model the forces and torques that drive the orbit and attitude evolution of such objects. The main influence modelled is solar radiation pressure (SRP), which is the interaction of solar electromagnetic radiation with the surface of an object, leading to both forces and torques that influence the orbital and attitude motion. Other influences, such as the gravitational field of the Earth, are also modelled.
Modern society has become heavily reliant upon space technologies for a wide variety of services, including communication, banking, weather prediction, Earth observation and global positioning. Since the first manmade satellite became operational in 1957, there have been over 5,000 space launches, resulting in a plethora of both operational and non-operational Space Resident Objects (SROs). The evolution of the number of SROs is shown in Figure 1.
The current constellation of over 1,000 operational satellites is at serious risk of collision with some 20,000 large space debris and countless smaller debris. A rendered image of the active satellites and all catalogued debris is shown in Figure 2. In the event of a few collisions, a cascading runaway effect could lead to the rapid cluttering of near-Earth space, which would cause collisions and the breakup of many active satellites in a short period of time. This is known as the Kessler syndrome. The broad field that deals with the observation and modelling of the near-Earth space environment is known as SSA.
Before decisions can be made regarding remediation of this problem, the current scenario must be better understood. This part of the problem can be approached in two ways: through observation, and through modelling. The former utilizes recent improvements in remote sensing techniques such as Satellite Laser Ranging (SLR), bistatic radar, optical observation networks, and potentially space-based observation, which enable more accurate tracking of the contents of near-Earth space. The latter involves taking such observations and applying laws of physics to predict the future movements of debris, and then comparing those predictions to later observations for validation of the modelling techniques.
The two approaches must be combined to give accurate predictions on what will happen in the future, and such a combination of observation and modelling is crucial in finding how to minimize the impact of space debris on the near-Earth space environment. Failure to deal with this problem could lead to a widescale breakdown of global infrastructure with dramatic impact to modern society
Finding the contents of near-Earth space and how they are moving is a difficult task - primarily due to the large number of physically similar objects and the vast volume within which these objects are orbiting. The problem of SSA has been highlighted as a key issue for future space activity, both by the United States Air Force (USAF) and by the European Space Agency (ESA). Initiatives such as ESA CleanSpace will lead to Active Debris Removal (ADR), which aims to deorbit larger debris to prevent further cluttering of near-Earth space. ESA aims to remove Envisat around 2021 as part of the CleanSpace initiative, as it is a large and heavy satellite that poses a significant risk for collision and cluttering of near-Earth space. Understanding its tumbling motion is of the utmost importance for such a mission to be successful.
This work was done by Hira Singh Virdee, University College London for the Air Force Research Laboratory. AFRL-0266
This Brief includes a Technical Support Package (TSP).
Space Debris Orbit and Attitude Prediction for Enhanced and Efficient Space Situational Awareness
(reference AFRL-0266) is currently available for download from the TSP library.
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