Throughout the history of interplanetary space travel, the Newtonian dynamics of the two-body problem have been used to design orbital trajectories to traverse the solar system. That is, that a spacecraft orbits only one large celestial body at a time. These dynamics have produced impressive interplanetary trajectories utilizing numerous gravity assists, such as those of Voyager, Cassini, Rosetta and countless others. But these missions required large amounts of delta-v for their maneuvers and therefore large amounts of fuel mass. As we desire to travel farther and more extensively in space, these two-body dynamics lead to impossibly high delta-v values, and missions become infeasible due to the massive amounts of fuel that they would need to carry. In the last few decades a new dynamical system has been researched in order to find new ways of designing mission trajectories: the N-body problem. This utilizes the gravitational acceleration from multiple celestial bodies on a spacecraft, and can lead to unconventional, but very useful trajectories. The goal of this thesis is to use the dynamics of the Circular Restricted Three-Body Problem (CRTBP) to design interplanetary transfer trajectories. This method of modelling orbital dynamics takes into account the gravitational acceleration of two celestial bodies acting on a spacecraft, rather than just one. The invariant manifolds of halo orbits about Sun-planet Lagrange points are used to aid in the transfer from one planet to another, and can lead into orbital insertion about the destination planet or flyby trajectories to get to another planet. This work uses this method of dynamics to test transfers from Earth to both Jupiter and Saturn, and compares delta-v and time of flight values to traditional transfer methods. Using the CRTBP can lead to reduced delta-v amounts for completing the same missions as two-body dynamics would. The aim of this work is to research if using manifolds for interplanetary transfers could be superior for some high delta-v missions, as it could drastically reduce the required delta-v for maneuvers. With this method it could be possible to visit more distant destinations, or carry more mass of scientific payloads, due to the reduced fuel requirements. Results of this research showed that using manifolds to aid in interplanetary transfers can reduce the delta-v of both departure from Earth and arrival at a destination planet. For transfers to Jupiter the delta-v for the interplanetary transfer was reduced by 4.12 km/s compared to starting and ending in orbits about the planets. For a transfer to Saturn the delta-v required for the interplanetary transfer was reduced by 6.77 km/s. These delta-v savings are significant and show that utilizing manifolds can lead to lower energy interplanetary transfer trajectories, and have the potential to be useful for high delta-v missions.

This thesis aims to investigate the potential of a transfer orbit using successive aerocaptures at Saturn and Titan to establish a science orbit around Titan. Titan is an Earth-like moon with a dense atmosphere and organic compounds present. It has many similarities with Earth that are useful to study such as superrotation. Superrotation is when the atmosphere rotates faster than the body it surrounds. In order to study Titan, we need to establish an orbit around it. The Saturn system is distant from Earth, 8.5 Astronomical Units (AU) which makes it difficult to reach from a time and velocity point of view. We propose to use an aerocapture at Saturn to intercept Titan with lower relative velocity in order to perform an aerocapture at Titan. The analysis was performed in primarily MATLAB to simulate the orbits. The results of this showed that we can aerocapture a spacecraft at Saturn and arrive at Titan within roughly 4 to 8 km/s relative velocity regardless of the incoming hyperbolic excess velocity at the Saturn system. This can be improve upon by using intermediate transfer orbits, such as bi-elliptics, to arrive with even lower relative velocities to Titan of as low as 1 km/s. The drag acceleration experienced during the Saturn aerocapture had peak values of between 0.2 and 1.4 g's and acceleration over 50% of the peak is experienced between 6.8 and 8 minutes. This capture method has the potential to make Titan more easily accessible and allow for scientific study of a clear target for improving our understanding of Earth-like processes on other bodies in our solar system. / Master of Science / This thesis aims to investigate the potential of a transfer orbit using successive aerocaptures at Saturn and Titan to establish a science orbit around Titan. Aerocapturing is utilizing the atmosphere of a body to slow down a spacecraft. Titan is an Earth-like moon with a dense atmosphere and organic compounds present. It has many similarities with Earth that are useful to study such as superrotation. Superrotation is when the atmosphere of a body rotates faster than the body it surrounds. In order to study Titan, we need to establish an orbit around it. The Saturn system is distant from Earth, 8.5 Astronomical Units (AU) which makes it difficult to reach from a time and velocity point of view. It takes a large amount of time to get there so we attempt to get there faster by increasing velocity. This means we arrive at the Saturn system with a large amount of velocity that we need to counter-act in order to orbit. We propose to use an aerocapture at Saturn to intercept Titan with lower velocity in order to perform another aerocapture at Titan to slow into an orbit. The analysis was performed in primarily MATLAB to simulate the orbits. The results of this showed that we can aerocapture a spacecraft at Saturn and arrive at Titan within roughly 4 to 8 km/s regardless of the incoming velocity to the Saturn system. This can be improve upon by using intermediate transfer orbits, after capturing at Saturn, to arrive with even lower velocities at Titan of as low as 1 km/s. The drag acceleration experienced during the Saturn aerocapture had peak values of between 0.2 and 1.4 g's and acceleration over 50% of the peak is experienced between 6.8 and 8 minutes. This is relatively gentle for an aerocapture and means the spacecraft likely will not require significant structural support. This capture method has the potential to make Titan more easily accessible and allow for scientific study of a clear target for improving our understanding of Earth-like processes on other bodies in our solar system.

In trajectory optimization, a common objective is to minimize propellant mass via multiple gravity assist maneuvers (MGAs). Some computer programs have been developed to analyze MGA trajectories. One of these programs, Parallel Global Multiobjective Optimization (PaGMO), uses an interesting technique known as the Island Model Paradigm. This work provides the community with a MATLAB optimizer, STOpS, that utilizes this same Island Model Paradigm with five different optimization algorithms. STOpS allows optimization of a weighted combination of many parameters. This work contains a study on optimization algorithm performance and how each algorithm is affected by its available settings. STOpS successfully found optimal trajectories for the Mariner 10 mission and the Voyager 2 mission that were similar to the actual missions flown. STOpS did not necessarily find better trajectories than those actually flown, but instead demonstrated the capability to quickly and successfully analyze/plan trajectories. The analysis for each of these missions took 2-3 days each. The final program is a robust tool that has taken existing techniques and applied them to the specific problem of trajectory optimization, so it can repeatedly and reliably solve these types of problems.

Critical aspects of spacecraft missions, such as component organization, control algorithms, and trajectories, can be optimized using a variety of algorithms or solvers. Each solver has intrinsic strengths and weaknesses when applied to a given optimization problem. One way to mitigate limitations is to combine different solvers in an island model that allows these algorithms to share solutions. The program Spacecraft Trajectory Optimization Suite (STOpS) is an island model suite of heterogeneous and homogeneous Evolutionary Algorithms (EA) that analyze interplanetary trajectories for multiple gravity assist (MGA) missions. One limitation of STOpS and other spacecraft trajectory optimization programs (GMAT and Pygmo/Pagmo) is that they require a defined encounter body sequence to produce a constant length set of design variables. Early phase trajectory design would benefit from the ability to consider problems with an undefined encounter sequence as it would provide a set of diverse trajectories -- some of which might not have been considered during mission planning. The Hybrid Optimal Control Problem (HOCP) and the concept of hidden genes are explored with the most common EA, the Genetic Algorithm (GA), to compare how the methods perform with a Variable Size Design Space (VSDS). Test problems are altered so that the input to the cost function (the object being optimized) contains a set of continuous variables whose length depends on a corresponding set of discrete variables (e.g. the number of planet encounters determines the number of transfer time variables). Initial testing with a scalable problem (Branin's function) indicates that even though the HOCP consistently converges on an optimal solution, the expensive run time (due to algorithm collaboration) would only escalate in an island model system. The hidden gene mechanism only changes how the GA decodes variables, thus it does not impact run time and operates effectively in the island model. A Hidden Gene Genetic Algorithm ( HGGA) is tested with a simplified Mariner 10 (EVM) problem to determine the best parameter settings to use in an island model with the GTOP Cassini 1 (EVVEJS) problem. For an island model with all GAs there is improved performance when the different base algorithm settings are used. Similar to previous work, the model benefits from migration of solutions and using multiple algorithms or islands. For spacecraft trajectory optimization programs that have an unconstrained fly-by sequence, the design variable limits have the largest impact on the results. When the number of potential fly-by sequences is too large it prevents the solver from converging on an optimal solution. This work demonstrates HGGA is effective in the STOpS environment as well as with GTOP problems. Thus the hidden gene mechanism can be extended to other EAs with members containing design variables that function similarly. It is shown that the tuning of the HGGA is dependent on the specific constraints of the spacecraft trajectory problem at hand, thus there is no need to further explore the general capabilities of the algorithm.

This thesis will focus on the performance of angles only initial orbit determi- nation (IOD) methods on observational data of low Earth orbit (LEO) CubeSats. Using data obtained by Lockheed Martin’s Space Object Tracking (SpOT) facil- ity, four methods: Gauss, Double-R, Gooding and Assumed Circular, will use different amounts of orbital arc to determine which methods perform the best in the short arc regime of less than 10 degrees of orbital arc. Once the best method for estimating the orbit is determined, there will be analysis on whether these IOD methods are accurate enough to predict a secondary observation session. Finally non-linear regression will be performed to determine if the error metrics follow a predictable trend based on how much orbital arc is seen by the observer. It was determined that above a certain amount of orbital arc, angles only IOD methods can reliably predict a secondary observation session to facilitate more observations. Below 4 degrees of orbital arc, which is around 60 seconds of ob- serving time for LEO objects, none of the methods were able to reliably predict a secondary observation session. The Assumed Circular method was the best method for observing LEO CubeSats because it forces the IOD solution to be circular, which limits the error in the shape of the orbit as the amount of orbital arc decreases. Finally, many metrics follow an exponential trend when compared to the orbital arc. Thus, the amount of orbital arc seen is a strong predictor for the accuracy of the angles only IOD solutions.

In October 2017, the first interstellar object, designated 1I/2017 U1 and more commonly referred to as Oumuamua, was detected passing through our solar system by the Pan-STARRS telescope, followed recently by the detection of 2I/Borisov in August 2019. These detections came much sooner than thought possible, and have redefined our understanding of the population of interstellar objects. With the construction of the next generation of powerful observatories, future detections are estimated to occur as frequently as two per year, and while there is significant scientific understanding to be gained from observing these objects remotely, a spacecraft sent to intercept one might be the only way to collect up-close, detailed information on the composition of extra solar object. The ideal mission scenario would be a combination flyby and impact as performed and proven feasible by the Deep Impact encounter with the comet Temple 1. A study has already been done showing that trajectories to interstellar objects are feasible with current chemical propulsion and a “launch on detection” paradigm, with an estimated 10 year wait time between favorable mission opportunities, assuming future detection capabilities. However, while a trajectory to one of these objects might be feasible, accurately performing a flyby and impacting an object with a hyperbolic orbit presents unprecedented navigational challenges. Spacecraft-target relative velocities can range between 10 km/s to 110 km/s with high phase angles between 90° and 180°. The goal of this thesis is to determine the required navigation hardware – an optical navigation camera and attitude determination system – which could provide high mission success probability for many potential encounter scenarios. This work is performed via a simulation program developed at the Jet Propulsion Laboratory that generates simulated images of a target during the terminal guidance phase of a mission, and feeds them into the algorithms behind autonomous navigation software (AutoNav) used for the Deep Impact mission. Observations are derived from the images and used to perform target-relative orbit determination and calculate correction maneuvers.

This thesis work presents the formulation for a tool developed in MATLAB to determine the mass of a space object from the fusion of astrometric and photometric data. The application for such a tool is to better model the mass estimation method used for high area-to-mass ratio objects found in high altitude orbit regimes. Typically, the effect of solar radiation pressure is examined with angles observations to deduce area-to-mass ratio calculations for space objects since the area-to-mass ratio can greatly affect its orbital dynamics. On the other hand, photometric data is not sensitive to mass but is a function of the albedo-area and the rotational dynamics of the space object. Thus from these two data types it is possible to disentangle intrinsic properties using albedo-area and area-to-mass and ultimately determine the mass of a space object. Three case studies were performed for the different orbit regimes: geosynchronous, highly elliptic, and medium earth orbit. The position states were either initialized with a two line element set or with initial orbit determination methods to simulate data which was run through an unscented Kalman filter to estimate the translational and rotational states of the space object as well as the mass an albedo area. In the geosynchronous and highly elliptic cases the tool was able to accurately predict the mass value to within 5kg of the true value based on a 95% confidence interval which will allow applications to understanding high area-to-mass objects with high certainty.

The information presented in the thesis is a continuation of the Spacecraft Trajectory Optimization Suite (STOpS). This suite was originally designed and developed by Timothy Fitzgerald and further developed by Shane Sheehan, both graduate students at California Polytechnic State University, San Luis Obispo. Spacecraft utilizing low-thrust transfers are becoming more and more common due to their efficiency on interplanetary trajectories, and as such, finding the most optimal trajectory between two planets is something of interest. The version of STOpS presented in this thesis uses Multiple Gravity-Assist Low-Thrust (MGALT) trajectories paired with the island model paradigm to accomplish this goal. The island model utilizes four different global search algorithms: a Genetic Algorithm, Differential Evolution, Particle Swarm Optimization, and Monotonic Basin Hopping. The first three algorithms were featured in the initial version of STOpS written by Fitzgerald [1], and were subsequently modified by Sheehan [2] to work with a low-thrust adaptation of STOpS. For this work, Monotonic Basin Hopping was added to aid the suite with the MGALT trajectory search. Monotonic Basin Hopping was successfully validated against four different test functions which had been used to validate the other three algorithms. The purpose of this validation was to ensure Monotonic Basin Hopping would work as intended, ensuring it would work in cooperation with the other three algorithms to produce a near optimal solution. After verifying the addition of Monotonic Basin Hopping, all four algorithms were used in the island model paradigm to verify MGALT STOpS’ ability to solve two known orbital transfer problem. The first verification case involved an Earth to Mars transfer with fixed thruster parameters and a predetermined time of flight. The second verification case involved a transfer from Earth to Jupiter via a Mars gravity assist; two different versions of the verification case were solved against trajectories produced by industry optimization software, the Satellite Tour Design Program Low-Thrust Gravity Assist and the Gravity Assisted Low-thrust Local Optimization Program. In the first verification case, MGALT STOpS successfully validated the Earth to Mars trajectory problem and found results agreeable to literature. In the second verification case, MGALT STOpS was partially successful in validating the Earth to Mars to Jupiter trajectory problems, and found results similar to literature. The final software produced for this work is a trajectory optimization suite implemented in MATLAB, which can solve interplanetary low-thrust trajectories with or without the inclusion of gravity assists.

This dissertation expands across three topics the geometric theory of phase space transit in the circular restricted three-body problem (CR3BP) and its generalizations. The first topic generalizes the low energy transport theory that relies on linearizing the Lagrange points in the CR3BP to time-periodic perturbations of the CR3BP, such as the bicircular problem (BCP) and the elliptic restricted three-body problem (ER3BP). The Lagrange points are no longer invariant under perturbation and are replaced by periodic orbits, which we call Lagrange periodic orbits. Calculating the monodromy matrix of the Lagrange periodic orbit and transforming into eigenbasis coordinates reveals that the transport geometry is a discrete analogue of the continuous transport geometry in the unperturbed problem. The second topic extends the theory of low energy phase space transit in periodically perturbed models using a nonlinear analysis of the geometry. This nonlinear analysis relies on calculating the monodromy tensors, which generalize monodromy matrices in order to encode higher order behavior, about the Lagrange periodic orbit. A nonlinear approximate map can be obtained which can be used to iterate initial conditions within the linear eigenbasis, providing a computationally efficient means of distinguishing transit and nontransit orbits that improves upon the predictions of the linear framework. The third topic demonstrates that the recently-discovered "arches of chaos" that stretch through the solar system, causing substantial phase space divergence for high energy particles, may be identified with the stable and unstable manifolds to the singularities of the CR3BP. We also study the arches in terms of particle orbital elements and demonstrate that the arches correspond to gravity assists in the two-body limit. / Doctor of Philosophy / Suppose that we have a spacecraft and we want to model its motion under gravity. Depending upon what trade-offs we are willing to make between accuracy and complexity, we have several options at our disposal. For example, the restricted three-body problem (R3BP) and its generalizations prove useful in many real-world situations and are rich in theoretical power despite seeming mathematically simple. The simplest restricted three-body problem is the circular restricted three-body problem (CR3BP). In the CR3BP, two masses (like a star and a planet or a planet and a moon) orbit their common center of gravity in circular orbits, while a much smaller body (like a spacecraft) moves freely, influenced by the gravitational fields that the two masses create. If we add in an extra force that acts on the spacecraft in a periodic, cycling way, the regular CR3BP becomes a periodically-perturbed CR3BP. Examples of periodically-perturbed CR3BP's include the bicircular problem (BCP), which adds in a third mass that appears to orbit the center of the system from a distance, and the elliptic restricted three-body problem (ER3BP), which allows the two masses to orbit more realistically as ellipses rather than circles. The purpose of this dissertation is to determine how to select trajectories that move spacecraft between places of interest in restricted three-body models. We generalize existing theories of CR3BP spacecraft motion to periodically-perturbed CR3BP's in the first two topics, and then we investigate some new areas of research in the unperturbed CR3BP in the third topic. We utilize numerical computations and mathematical methods to perform these analyses.

Spacecraft relative motion modeling and control promises to enable or augment a wide range of missions for scientific research, military applications, and space situational awareness. This dissertation focuses on the development of novel, optimization-based, control design for some representative relative-motion-enabled missions. Spacecraft relative motion refers to two (or more) satellites in nearly identical orbits. We examine control design for relative configurations on the scale of meters (for the purposes of proximity operations) as well as on the scale of tens of kilometers (representative of science gathering missions). Realistic control design for satellites is limited by accurate modeling of the relative orbital perturbations as well as the highly constrained nature of most space systems. We present solutions to several types of optimal orbital maneuvers using a variety of different, realistic assumptions based on the maneuver objectives. Initially, we assume a perfectly circular orbit with a perfectly spherical Earth and analytically solve the under-actuated, minimum-energy, optimal transfer using techniques from optimal control and linear operator theory. The resulting open-loop control law is guaranteed to be a global optimum. Then, recognizing that very few, if any, orbits are truly circular, the optimal transfer problem is generalized to the elliptical linear and nonlinear systems which describe the relative motion. Solution of the minimum energy transfer for both the linear and nonlinear systems reveals that the resulting trajectories are nearly identical, implying that the nonlinearity has little effect on the relative motion. A continuous-time, nonlinear, sliding mode controller which tracks the linear trajectory in the presence of a higher fidelity orbit model shows that the closed-loop system is both asymptotically stable and robust to disturbances and un-modeled dynamics. Next, a novel method of computing discrete-time, multi-revolution, finite-thrust, fuel-optimal, relative orbit transfers near an elliptical, perturbed orbit is presented. The optimal control problem is based on the classical, continuous-time, fuel-optimization problem from calculus of variations, and we present the discrete-time analogue of this problem using a transcription-based method. The resulting linear program guarantees a global optimum in terms of fuel consumption, and we validate the results using classical impulsive orbit transfer theory. The new method is shown to converge to classical impulsive orbit transfer theory in the limit that the duration of the zero-order hold discretization approaches zero and the time horizon extends to infinity. Then the fuel/time optimal control problem is solved using a hybrid approach which uses a linear program to solve the fuel optimization, and a genetic algorithm to find the minimizing time-of-flight. The method developed in this work allows mission planners to determine the feasibility for realistic spacecraft and motion models. Proximity operations for robotic inspection have the potential to aid manned and unmanned systems in space situational awareness and contingency planning in the event of emergency. A potential limiting factor is the large number of constraints imposed on the inspector vehicle due to collision avoidance constraints and limited power and computational resources. We examine this problem and present a solution to the coupled orbit and attitude control problem using model predictive control. This control technique allows state and control constraints to be encoded as a mathematical program which is solved on-line. We present a new thruster constraint which models the minimum-impulse bit as a semi-continuous variable, resulting in a mixed-integer program. The new model, while computationally more expensive, is shown to be more fuel-efficient than a sub-optimal approximation. The result is a fuel efficient, trajectory tracking, model predictive controller with a linear-quadratic attitude regulator which tracks along a pre-computed ``safe'' trajectory in the presence of un-modeled dynamics on a higher fidelity orbital and attitude model. / Ph. D.