No description available.

The word 'rendezvous' implies a pre-arranged meeting between two entities for a specific purpose. This term is used in the study of spacecraft operations, to describe a set of maneuvers performed by two spacecraft in order to achieve a match in position and velocity. The term 'orbital rendezvous' applies to rendezvous between spacecraft in earth-centered orbits. Considering its obvious scope for application in the assembly, maintenance and retrieval of earth satellites, the importance of orbital rendezvous towards maintaining a sustained presence in space can be easily appreciated. This particular study deals with the development of a guidance scheme for an orbital rendezvous operation, wherein only one of the spacecraft, called the chaser, is assumed to be provided with a capability to maneuver, while the other spacecraft, the target, is assumed to be thrust-free or passive. There is presently a lot of interest in autonomous trajectory planning and guidance schemes for orbital rendezvous missions. Autonomy here, refers to the absence of ground supervision and control over the on-board planning and guidance process, and is expected to result in greater mission flexibility and lower operating costs. The terms trajectory planning and guidance collectively refer to the optimization process used to determine minimum-fuel trajectories, and the means employed to make the spacecraft follow them, based on navigational updates. The challenge lies mainly in making the autonomous scheme real-time implementable, and at the same time compatible with the limited computational capabilities available on-board. It is well known that a large part of the computation times and costs, when determining optimal trajectories, are taken up by (1) the prediction of spacecraft motion using numerical integration schemes, and (2) the use of iterative numerical techniques to solve the non-linear, coupled system of equations obtained as boundary conditions in the trajectory optimization problem. There exists on the other hand, a wealth of results from analytical investigations into the motion of spacecraft, that can be profitably utilized by use of suitable assumptions, to reduce computation times and costs relating to trajectory prediction. The present thesis seeks to follow this course, while trying to ensure that the assumptions made do not influence in a negative manner the accuracy of the guidance scheme. The assumptions to be described below are based on the division of the total rendezvous maneuver into sub-phases. The trajectory optimization problems for the individual sub-phases are first considered independent of one another. A method is then found to combine the two sub-phases in an optimal manner. The initial or the homing phase of the rendezvous maneuver, consists of an open-loop orbit transfer, intended to place the chaser within a 'window of proximity' spanning a few hundreds of kilometers, of the target. In order to avoid time consuming numerical integration of the non-homogeneous, non-linear central force-field equations of motion, an impulsive thrust model is assumed. A parametric optimization method is used to determine the location, orientation and magnitude of the impulses for a minimum-fuel rendezvous transfer, as it is well known that parametric optimization methods are robust compared to the more general functional optimization methods. A two-impulse transfer is selected, knowing that at least two-impulses are required for a rendezvous maneuver, and that methods are available if necessary, to obtain optimal multi-impulse trajectories from a two-impulse solution. The total characteristic velocity, a scalar cost function related to fuel-consumption, is minimized with respect to a set of independent variables. The variables chosen in this case to determine the rendezvous transfer are (1) the transfer angle θc defining an initial coast in the chaser orbit C by the chaser, (2) the transfer angle θs defining a coast by the target to the position of the second impulse in the target orbit S and (3) a parameter (say p ) that determines the shape of the transfer orbit T between the first and second impulses.

While human presence in cislunar space continues to expand, so too does the demand for `lightweight' automated on-board processes. In nonlinear dynamical environments, computationally efficient guidance strategies are challenging. Many traditional approaches rely on either simplifying assumptions in the dynamical model or on abundant computational resources. This research employs reinforcement learning, a subset of machine learning, to produce a controller that is suitable for on-board low-thrust guidance in challenging dynamical regions of space. The proposed controller functions without knowledge of the simplifications and assumptions of the dynamical model, and direct interaction with the nonlinear equations of motion creates a flexible learning scheme that is not limited to a single force model. The learning process leverages high-performance computing to train a closed-loop neural network controller. This controller may be employed on-board, and autonomously generates low-thrust control profiles in real-time without imposing a heavy workload on a flight computer. Control feasibility is demonstrated through sample transfers between Lyapunov orbits in the Earth-Moon system. The sample low-thrust controller exhibits remarkable robustness to perturbations and generalizes effectively to nearby motion. Effective guidance in sample scenarios suggests extendibility of the learning framework to higher-fidelity domains.

<div>In order to answer the most pressing scientific questions about the two Martian moons, Phobos and Deimos, new remote sensing observations are required. The best way to obtain global high resolution observations of Phobos and Deimos is through dedicated missions to each body that utilize close-proximity orbits, however much of the orbital tradespace is too unstable to realistically or safely operate a mission.</div><div><br></div><div>This thesis explores the dynamics and stability characteristics of trajectories near Deimos. The family of distant retrograde orbits that are inclined out of the Deimos equatorial plane, known as quasi-satellite orbits, are explored extensively. To inform future mission design and CONOPS, the sensitivities and stability of distant retrograde and quasi-satellite orbits are examined in the vicinity of Deimos, and strategies for transferring between DROs are demonstrated. Finally, a method for designing quasi-satellite science orbits is demonstrated for a set of notional instruments and science requirements for a Deimos remote sensing mission.<br></div>

<p dir="ltr">The future of the global economy lies in space. As the economic and scientific benefits from space become more accessible and apparent to the public, the demand for more spacecrafts will only increase. However, simply using the current space architecture to sustain any major activities past low Earth orbit is infeasible. The limiting factor of relying on ground operators via the Deep Space Network will blunt future growth in cislunar space traffic as the bandwidth is insufficient to satisfy the needs of every spacecraft in this domain. For this reason, spacecrafts must begin to operate autonomously or semi-autonomously for operators to be able to manage more missions at a given time. This thesis focuses on the guidance and navigation policies that could help vehicles such as logistical or resupply spacecrafts perform their rendezvous autonomously. It is found that using GNSS signals and Moon-based optical navigation has the potential to help spacecrafts perform autonomous orbit determination in near-Moon trajectories. The estimations are high enough quality such that a stochastic controller can use this navigation solution to confidently guide the spacecraft to a target within a tolerance before proximity operations commence. As the reliance on the ground is shifted away, spacecrafts would be able to operate in greater numbers outside of Earth's lower orbits, greatly assisting humanity's presence in space. </p>