The Astrodynamics Group is a lively and active group researching into space mission design and space surveillance and tracking.

Our main goal in mission design is to exploit the nonlinearities of the dynamics and optimal control theory to reduce mission costs and enable new mission concepts. We apply our research to a variety of problems, including low-thrust and impulsive interplanetary transfers, formation flying design and control, rendezvous and docking, remote sensing missions.

Our activity in space surveillance and tracking is aimed at enabling the sustainable use of space. The research is focused on improving the capabilities in predicting the future position of space resident objects (RSO), the way in which we observe them and determine their orbits to build and maintain the RSO catalogue. We do research to improve the accuracy of conjunctions analysis tools, which are needed to avoid in-space collisions and to enable safer and more cost-effective spacecraft operations. We study methods to improve re-entry predictions to reduce on-ground casualty risks and low-cost options for spacecraft end-of-life disposal to limit the probability of in-space collisions, thus enabling a sustainable use of space.

The work done by the group is multidisciplinary, where the mix of backgrounds varies. We attract mathematicians looking at non-linear dynamical problems, electronic engineers for the design and integration of hardware for the testing of our algorithms, software engineers for the development of complex AOCS software systems and computer scientists interested in behavioural models for the scheduling and cooperation of multiple spacecraft.

The group has had a long association with SSTL and contributed to the successes of a number of SSTL missions in the orbit and attitude maintenance of their satellite. Our research has been funded also by other private and public organisations including by European Space Agency, European Commission, and European Office of Aerospace Research and Development.

Our research

New orbit propagation techniques are studied to efficiently propagate a large population of resident space objects (RSO). These new techniques are based on the combination of semi-analytical propagators and high order Taylor expansions via Differential Algebra techniques.

To enable safe operations, we need to observe and determine the orbits of RSO of small dimensions (cm size). Determining if two or more observations belong to a same object and establishing a good orbit with single-pass observations are two key challenges of initial orbit determination.

Comparison between a fully numerical propagation (AIDA) and semi-analytical propagation (DA) of a re-entering object, SA propagation is order of magnitude faster.
Comparison between admissible region approach (region enclosed by the red and the orange curve) and the admissible orbits approach (small black rectangle).

Conjunctions between resident space objects (RSO) occur frequently in orbit. Spacecraft operators need to process a large number of conjunction warnings and decide when collision avoidance manoeuvres are needed.

The objective is to improve the accuracy of collision probability computation with advanced Monte Carlo methods, thus reducing the number of false alarms. When the collision probability between two RSO is high a collision avoidance manoeuvre needs to be design and executed. Our objective is to optimise these maneuvers such that a safety distance is achieved with the minimum consumption of propellant.

The use of advanced Monte Carlo methods such as Subset Sampling (SS) enables the computation of low collision probability with a reduced number of samples NT.

Current re-entry predictions of RSO are quite inaccurate, i.e. an error of about 20% in the time to re-entry. The goal is to improve the models for the estimation of the ballistic coefficient of re-entering objects, thus reducing the uncertainty in the re-entry epoch and the on-ground casualty risks.

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Ballistic coefficient (BC) estimation from TLEs (left) and re-entry prediction accuracy for 100 spent rocket bodies in GTO (right).

Moving the spacecraft to graveyard orbit or on an Earth’s re-entry path are two viable options for end-of-life disposal. The objective is to minimise the propellant required by these manoeuvres taking full advantage of orbit perturbations, thus enabling an increased missions economic return.

We have applied global trajectory optimisation to study the end-of-life disposal of Lagrangian point and high elliptic orbit missions and navigation constellations.

End-of-life disposal for Integral spacecraft exploiting J2 and luni-solar resonances, re-entry (left) and graveyard (right).

Launching a spacecraft is expensive. Reducing the launch mass is one of the objective of space mission analysts. This can be achieved by optimising the orbital transfers required to achieve the operative orbit, thus allowing the minimisation of the propellant mass.

We apply optimal control theory to a range of different trajectory optimisation problems including: formation flying; impulsive and low-thrust transfers in the two- and three-body dynamics; aero-gravity assists and aerocapture trajectories optimization; end-of-life disposal design; and lunar and planetary landing.

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Low-thrust transfer to a Moon L2 halo orbit (left) and Earth-Apophis sample return mission (right).

Space mission design is a complex problem involving different disciplines, a large number of variables, constraints and often clashing objectives. We apply multidisciplinary optimisation to find optimal solution to such complicated problems.

Applications include: the optimization of space vehicles involved in atmospheric manoeuvres; the coupled trajectory and spacecraft subsystems optimization; the design of active space debris removal devices; the optimisation of space debris observation strategy sensor network design.

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Pareto front of vehicles optimized for Mars aerocapture (left) and different solutions for aerogravity-assisted maneuvers at Mars (right).

Contact us

Find us

Surrey Space Centre
BA building
University of Surrey