Edoardo Ciccarelli

PLATOR is a new electrothermal thruster for space logistics applications, developed by the University of Surrey and the University of Leicester. This paper describes the technology behind the development of the thruster and presents a mission scenario where a PLATOR-propelled spacecraft is used to capture and de-orbit the European Space Agency (ESA)'s Envisat satellite. The orbital transfer trajectory is designed using a time-optimal control approach, and the spacecraft's state vector's uncertainties are assessed through a covariance analysis. A navigation analysis is then performed to evaluate the spacecraft's capability to autonomously track its motion during the transfer using GPS measurements. Finally, a target proximity phase is then simulated to demonstrate the spacecraft's capability to rendezvous and dock with Envisat, using the uncertainties obtained from the covariance analysis, showing the potential of the PLATOR thruster for in-orbit servicing and active debris removal applications.

Understanding the internal composition of a celestial body is fundamental for formulating theories regarding its origin. Deep knowledge of the distribution of mass under the body's crust can be achieved by analyzing its moments of inertia and gravity field. In this regard, the two moons of the Martian system have not yet been closely studied and continue to pose questions regarding their origin to the space community; thus, they deserve further characterization. The Martian Moons eXploration mission will be the first of its kind to sample and study Phobos over a prolonged period. This study aims to demonstrate that the adoption of periodic and quasi-periodic retrograde trajectories would be beneficial for the scientific value of the mission. Here, a covariance analysis was implemented to compare the estimation of high-order gravitational field coefficients from different orbital geometries and for different sets of processed observables. It was shown that the adoption of low-altitude non-planar quasi-satellite orbits would help to refine the knowledge of the moon's libration angle and gravitational field.

The Martian Moons eXploration mission will be the first of its kind to sample and study Mars's moon Phobos for a prolonged period of time. The aim of this work is to show that the adoption of periodic and quasi-periodic retrograde trajectories would be beneficial for the scientific return of MMX. A consider covariance analysis is hereby implemented in order to compare the estimation of high-order gravitational field coefficients from different orbital geometries and processing different sets of observables. It is shown that low-altitude non-planar quasi-satellite orbits would refine the knowledge of the moon's gravity field.

Guidance and navigation algorithms play a crucial role in ensuring a successful spacecraft mission. This work proposes a full guidance and navigation algorithm based on differential algebra successive convex programming technique (SCVX). By leveraging the high-order expansions around the reference trajectory it is possible to enhance the computational efficiency of convex-based guidance and navigation algorithms. The high-order expansion enables to capture of the non-linearities in the estimation and guidance problems without sacrificing the robustness of the algorithms. Monte Carlo analyses are carried out to assess the benefits of recom-puting the guidance from the estimated state with this new high-order approach while being robust to uncertainties and errors.

Proximity operations around Phobos are critical for the Martian Moons eXploration (MMX) mission, and accurate knowledge of the spacecraft's trajectory is required to perform scientific observations and maximise the chances of understanding the moon's internal structure. Possible solutions to implement autonomous navigation around Phobos while orbiting at lower altitudes are presented in this paper and compared with standard navigation techniques. For this purpose, our analyses will compare the level of knowledge achievable once the connection with the Deep Space Network is cut off, showing what can be achieved without ground support, using only information that can be collected and processed onboard, mainly lidar and optical data. Different strategies to build a map of the moon's surface's landmarks are also discussed, demonstrating how this operation can be performed autonomously by the spacecraft and how landmark-based navigation is paramount in estimating the spacecraft's state. Finally, the capability of this setup to observe the moon's gravity field will be assessed, returning precious information for the future geodetic investigations of the Martian Moons eXploration mission around Phobos.

Despite the advantages of very-low altitude retrograde orbits around Phobos, questions remain about the efficacy of conventional station-keeping strategies in preventing spacecraft such as the Martian Moons eXploration from escaping or impacting against the surface of the small irregular moon. This paper introduces new high-fidelity simulations in which the output of a sequential Square-Root Information Filter is combined with recently developed orbit maintenance strategies based on differential algebra and convex optimization methods. The position and velocity vector of the spacecraft are first estimated using range, range-rate, and additional onboard data types such as LIDAR and camera images. This information is later processed to assess the necessity of an orbit maintenance maneuver based on the estimated relative altitude of MMX about Phobos. If a maneuver is deemed necessary, the state of the spacecraft is fed to either a successive convex optimization procedure or a high-order target phase approach capable of providing sub-optimal station-keeping maneuvers. The performance of the two orbit maintenance approaches is assessed via Monte Carlo simulations and compared against work in the literature so as to identify points of strength and weaknesses.