Astrodynamics

Understanding the motion of objects in space is a core area of space engineering that underpins and enables space exploration. Yet, except for very few occasions (Kepler’s two-body problem and Euler’s attitude equations under torque-free motion assumptions), the evolution of a satellite’s orbit cannot be known in closed-form.

We research into advanced numerical continuation techniques that can help us better understand and organise the dynamics of high-fidelity astrodynamics problems via entire families of periodic and quasi-periodic orbits. Dynamical “highways’’ known as stable and unstable manifolds that emanate from some of these solutions are also leveraged by our team in order to identify ballistic transfers for lunar and deep-space exploration.

Launching a spacecraft is expensive. Improving the efficiency of any spacecraft mission is a key objective of any space mission analyst. 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 rendezvous and docking; impulsive and low-thrust transfers in two- and three-body problems; orbit maintenance of periodic and quasi-periodic orbits and interplanetary trajectory design.

Similarly to our smartphones, which can help us pinpoint our location on Earth via embedded GNSS receivers, satellites in low Earth orbit can also use GNSS constellations (GPS, Galileo, GLONASS,…) to triangulate their position in space. However, things become a lot trickier when GNSS constellations cannot be relied upon or communications with Earth ground stations become difficult owing to physical and/or budget constraints. 

 

By merging knowledge from a variety of engineering topics (probability and statistics, estimation theory, data fusion and processing, computer vision and machine learning), our team aims at analysing orbit and attitude data in order to estimate the position, velocity, and attitude coordinates of a satellite. Our goal is to advance absolute and relative navigation techniques for effective and autonomous estimation algorithms that enable spacecraft operations. These include (but are not limited to) square-root information and unscented Kalman filters for active debris removal and small body exploration missions.

An emerging trend in space mission design is the replacement of large monolithic spacecraft with a group of small cost-effective satellites that cooperate in space to fulfill modern and innovative mission objectives. Pivotal to the success of this trend (as well as of related topics such as active debris removal) is a deep understanding of the relative dynamics (orbital and attitude alike) between two or more vehicles in strongly perturbed dynamical environments.

 

We combine our multi-disciplinary background with Surrey Space Centre’s ad-hoc research facilities to improve upon existing methods of spacecraft formation flying and advance new and disruptive technologies for robust, fuel-efficient, and autonomous proximity operations.

Space mission design is a complex problem involving different disciplines, many variables, constraints and, sometimes, even clashing objectives. We apply multi-disciplinary optimisation strategies to engineer optimal solutions to innovative mission concepts and complicated trajectory problems. 

 

Applications include trajectory design near small irregular bodies (asteroids, comets, and small planetary moons); feasibility studies of small scientific missions under trajectory, payload, and system constraints; active debris removal and space debris observation strategies and interplanetary CubeSats.