To accomplish the dream of continuous presence on the Moon, humanity has to face many challenges. A major one is to provide continuous electrical power to all the necessary installations on the surface during the long lunar nights or in the dark polar craters. This study explores the design and optimization of one solution to this problem: space-based solar power (SBSP). The SBSP system consists of one or more solar power satellites, generating power and transmitting it remotely to a receiver on the surface.

Two system concepts are investigated: a constellation of satellites in lunar elliptical frozen orbits and a single satellite in the L1 Lagrange point. Both concepts are designed to deliver at least 100 kW of continuous power to the lunar surface through laser power transmission. The study combines sizing of the spacecraft, the ground element, propagation of the final trajectory and a detailed model of the transmission efficiency to find an optimal design for both concepts. The space elements make use of concentrated photovoltaics, an active fluid loop and a high-power laser, while the ground elements are build out of modular elements of either stretched lens arrays or heat pipe cooled laser power converters.

Selected subsystems of the lunar orbit constellation have been designed in more detail, resulting in a 7 satellite constellation of 2247 kg per satellite a 816 kg modular ground element. Both the Lagrange point and lunar orbit architectures outperform alternative power systems (nuclear & microwave-based SBSP) in terms of launch costs by almost an order of magnitude on average.

Over the past decade, there have been significant advancements in both the availability and diversity of satellite navigation systems, on both regional and global scales. The growing significance of GNSS across various fields has led not only to the modernisation of existing systems like the GPS and GLONASS, but also to the creation of new ones such as Galileo. The Navigation Support Office (NSO) operates as a vital component within the European Space Agency, specialising in the precise utilisation of navigation satellite systems. In 2024, NSO underwent a revision of its GNSS processing system, which resulted in a state-of-the-art GNSS processing framework known as CHAMP, Consolidated High Accuracy Multi-GNSS Processing, which is based on constellation-wise data processing and normal equation stacking to efficiently generate GNSS products for all major navigation constellations. This new approach enables internal comparisons between individual constellation solutions and the consolidated multi-GNSS solution, revealing unique characteristics of each constellation and demonstrating the enhanced impact of combining them in critical ways.

This thesis explores and addresses key inconsistencies in the processing of multi-GNSS solutions within the Navigation Support Office, with a particular focus on producing accurate single-constellation solutions that can be reliably combined into a coherent multi-constellation framework. To tackle these inconsistencies, a comprehensive Python-based programme has been developed as an extension of the CHAMP framework, enabling a more efficient and structured approach for analysing large-scale GNSS data. As a result, this new tool provides the basis needed to identify anomalies, track trends, and address inconsistencies across various constellations during the combination process, as a post-processing analysis or within the operational pipeline. The core of this research involves a detailed examination of the parameters estimated in the NSO GNSS precise orbit determination, both in terms of individual and combined multi-GNSS solutions, including Earth orientation parameters, satellite state vectors, ground station positions, clock biases, and empirical accelerations, among others.

The investigation lead to significant inconsistencies in the Length of Day estimates of the individual GPS constellation, affecting the accuracy of the combined multi-GNSS solution. These issues are compounded by the combination of the large weight given to the GPS constellation in the combination due to its low variability, and the GPS non-gravitational a priori models, specially regarding forces like solar radiation pressure, which have been demonstrated to be not as refined as those for other constellations. Additionally, the tuning of empirical accelerations has shown that there is room for improvement to better reflect satellite dynamics.

In conclusion, several key enhancements were identified and proposed to improve the overall performance and reliability of the combined multi-GNSS solution, and subsequently improve the quality of the NSO GNSS products. These mainly comprise the comparison of different non-gravitational a priori models combined with the fine-tuning of empirical accelerations, allowing for a more robust integration of single-constellation solutions into a cohesive multi-constellation framework. Ultimately, recommendations on the way forward are given to create new models based on the results shown on this thesis

Solar sailing is a promising propellantless propulsion method that employs large reflective surfaces to harness solar radiation pressure for spacecraft propulsion. Despite the fact that several solar-sail near-Earth missions will launch in the coming years, there is notable lack of published studies on the uncertainties associated with missions of this kind. This thesis addresses this gap in knowledge by quantifying uncertainties related to the solar sail's optical coefficients, structural deformations, and attitude profiles. Through two uncertainty propagation methods, namely Monte Carlo simulations and the Gauss von Mises method, the study reveals the significant impact of the optical coefficient uncertainties on mission performance. The results indicate a worst-case 3-sigma uncertainty of 8.1% in altitude gain and 16.5% uncertainty in inclination gain for the NEA Scout solar sail model. Specularity coefficient uncertainty emerges as the primary driver of performance uncertainty among the analyzed optical coefficients. Structural deformation, on the other hand, exerts minimal impact. Uncertainty in the attitude profile is modelled through Ornstein-Uhlenbeck processes and is found to impact mean mission performance as well as introduce performance uncertainty. Overall, this work demonstrates the critical importance of characterizing uncertainties and provides insights crucial for mission planning and decision-making.

The optimization of interplanetary, low-­thrust trajectories is a computationally expensive aspect of preliminary mission design. To reduce the computational burden associated with it, surrogate models can be used as cheap approximations of the original fitness function. Training the surrogate models in a fully online manner can be done to remove the need of having previously generated datasets, which is another source of computational cost. The Sims­-Flanagan transcription is used to model an Earth-Mars transfer which is optimized through different optimization routines. The development of a C++ library with machine learning tooling was initiated, containing implementations for Generalized Regression Neural Networks (GRNNs) and Radial Basis Function Networks (RBFNs) that are used in global and local surrogates, respectively, having their hyperparameters tuned through cross-­validation. A surrogate model was constructed using Differential Evolution (DE) operators and an uncertainty-based infill criterion for the global search phase, and approximation of the derivative of the original fitness function which is provided to SNOPT (Sparse Nonlinear Optimizer), in the local search phase. An ablation study was performed to assess how each of the components of the surrogate model contribute to the results. It was verified that neither the derivative information nor the local search as a whole led to better results. The surrogate model was also outperformed by the standard optimization strategy found in literature, Monotonic Basin Hopping (MBH). Two new surrogate models incorporating ideas of this strategy were created, with one of them outperforming every other model that was tested. Despite not having performed a full study of the computational effort due to the simulations having been run in a server with a variable load, the new models present better results for similar amounts of fitness function evaluations. A Wilcoxon rank-­sum test was performed to assess whether the results have statistical significance, leading to the conclusion that a surrogate model can be used to improve the optimization of low-­thrust trajectories modeled with the Sims­-Flanagan transcription when inserted in a monotonic basin hopping optimization scheme.

Single-Stage-To-Orbit (SSTO) launch vehicles are capable of reaching orbit while being potentially fully reusable. A technology capable of enabling SSTO access to space is the air-breathing engine, which has a high specific impulse and low thrust-over-weight (T/W) ratio compared to conventional rocket engines. This necessitates the use of a Horizontal Take-off and Horizontal Landing (HTHL) launch vehicle with a lifting surface, which enables banking maneuvers that can manipulate the orbital Right Ascension of the Ascending Node (RAAN) that the space plane achieves. This means that the space plane is capable of advancing or delaying its time of launch, while still achieving a similar orbital RAAN. This effectively increases the launch window even if a precise orbit insertion is necessary.

This thesis answers the question what the fuel-optimal ascent trajectory is for a space plane that would extend its launch window. In order to answer this question, the full six DoF equations of motion have been defined to simulate the ascent trajectory of a space plane. Additionally, a robust Guidance and Control system is developed that can use the nonlinear translational and rotational equations of motion.

For several launch times, ranging from two hours earlier to two hours later than the nominal launch time, the ascent trajectory has been optimized that included a banking maneuver. It was found that at the cost of propellant, it is possible to have a launch time delayed are advanced by as much as two hours, which means that the space plane can manipulate the RAAN by ± 30 degrees. The extra propellant cost can be related to increased drag losses during the banking maneuver.

The applications for which the data from Earth observation satellites can be used are dependent on the precision and accuracy of the position of the satellite. Hence, precise orbit determination of satellites is crucial for the success of Earth observation satellites like the Sentinel family of satellites. TU Delft is an analysis center of the Copernicus precise orbit determination Quality Working Group and provides orbit solutions of Sentinel satellites for the external validation of the Sentinel orbits computed by the Copernicus Precise Orbit Determination Service. The GIPSYX/RTGx software is used for orbit determination using a reduced dynamic approach.

Existing research has focused on the overall accuracy of the orbit solutions to improve orbit accuracy. However, knowledge of the overall accuracy cannot provide much information about modeling errors. In this research, a data analysis approach was taken to aid the identification of the sources of errors in TU Delft's precise orbit determination strategy of the Sentinel satellites. From a thorough study of the precise orbit determination strategy, a set of parameters were selected for analysis, and a database was created for each satellite. Data analysis methods were customized to create a data analysis framework for the orbit determination data analysis. This framework was applied to the orbit determination data of Sentinel 1A, 1B, 2A, 2B, 3A, and 3B satellites, and the results were interpreted.

The two most common sources of error speculated were errors in the antenna phase center offset or phase center variations, and errors in the location of the center of mass of the satellite. Recommendations were issued regarding ways to confirm the error sources. A significant (> 95 %) correlation was observed between drag coefficient and geomagnetic activity index (Ap index) which shows the improper modeling of geomagnetic activity in the DTM2000 atmospheric density model.

The use of low-thrust propulsion for interplanetary missions requires the implementation of new methods for the preliminary design of their trajectories. This thesis proposes a method using the Monotonic Basin Hopping global optimization algorithm to find feasible trajectories with optimum use of the mass of fuel for the case in which the trajectory is modeled using the Sims-Flanagan transcription method. Due to the large computational time required to find the global optimum, Artificial Neural Networks have been used to predict the objective value and feasibility terms of the local minimum. Therefore, the procedure to set up a working regression Artificial Neural Network is studied as well as its transferability to predict values outside the trained limits and for different missions. In addition to this, the use of pre-training is analyzed to improve the performance of the network without increasing the size of the training database.

Re-entry mission design remains an active field of study to safely return space missions back to Earth. With the developments in on-board computers, mission design and especially optimization of these missions has been performed numerically at an increasing rate at the cost of computing power. Analytical second-order methods have previously been shown to provide accurate results for mission design with less computational effort, but have not been applied to mission optimization. The analytical method was tested and shown to provide good results for a range of initial conditions. During optimization, restrictions arising from their derivation show that fundamental problems remain for application in mission optimization as the entry state cannot be freely defined. Additionally, two new optimization algorithms have been tested for re-entry mission optimization, a variable chromosome length algorithm and the Multi-objective Hypervolume-based Ant Colony Optimizer, both are found to provide results similar to the MOEA/D algorithm.

Various machine learning algorithms have been applied to find optimal lowthrust
satellite trajectories, however, no fair comparison of their accuracy has been made yet. In this paper, two common and promising supervised machine learning algorithms are compared for their regression capacities:
the artificial neural network and the Gaussian process. A grid search is performed to evaluate the performance of the algorithms on different datasets, varying the input features for training, and the hyperparameters of the algorithms. The best performing Gaussian process and artificial neural network are applied as surrogate in a model that optimizes a trajectory from Earth to Mars using a differential evolution optimization strategy. The performance of the models is evaluated on both the Euclidean distance between the inputs corresponding to the predicted minima of the surrogate method and the nearest local minimum obtained with the shaping method, and the accuracy of the predicted Δ푉 budget required. For both quantities, the Gaussian process outperforms the artificial neural network. The minimum required Δ푉 budget to reach Mars was predicted more accurately, and the duration of the trajectory and the best moment to launch were found more often and accurately as well.

Low-thrust propulsion's main advantage is its efficient propellant usage. This holds for manoeuvres as well as for major orbital changes, both for LEO/MEO/GEO satellites and for interplanetary missions. In designing such missions, extensive numerical models as well as less demanding analytic first-order approximations can be used. A specific kind of the latter category of methods are called shape-based methods. TU Delft's Astrodynamic Toolbox (TUDAT) contains the framework for shape-based methods with spherical shaping and hodographic shaping already implemented for use by students and staff. Having more shape-based method available allows for a more versatile toolbox and combining several shapes with for example coasting would lead to more attractive and efficient transfers. This thesis provides the theory required for the implementation of both exponential sinusoids and the sixth order inverse polynomials with 3D capabilities. These methods have been successfully implemented, verified and validated into the TUDAT shape-based framework.
The four shape-based methods have been applied to an Earth-Tempel-1 transfer for start dates from 2020 to 2025 and time of flights of 100 to 8900 days. It is found that the following order can be established with respect to their lowest ΔV, based on both an unoptimised grid search and global optimisation: Inverse polynomial shaping (10.51 km/s), Spherical shaping (11.71 km/s), Exponential shaping (13.09 km/s), Hodographic shaping (26.22 km/s).
Optimising for ΔV and peak thrust acceleration with the Earth-Tempel-1 transfer including a coasting arc between two powered arcs for inverse polynomials and spherical shaping compared to the standard transfer, yields the following results: Trajectories with similar and lower ΔVs, similar and lower peak thrust for the same ΔV and similar and longer time of flights. In conclusion coasting arcs provide more flexibility in terms of start date, time of flight and peak acceleration thrust for a marginal increase or decrease in ΔV.

Jupiter is the most visited outer solar system planet, but the exact variation in atmospheric properties along its disk remains largely a mystery. This is where polarimetry fits into the picture. Its added value to spectrometry by additionally measuring the polarisation degree and direction of light makes it a suitable remote sensing tool for the characterisation of planetary atmospheres. It can potentially be used to detect and characterise exoplanets as starlight is originally unpolarised [Kemp et al., 1971] while light reflecting from an object is not. The degree of polarisation is sensitive to the atmospheric properties and its coupling with the wavelength, phase angle and absorption are used to derive the approximate upper atmospheric structure of Jupiter. For this purpose, polarimetric observations of the Torino Polarimeter are compared to the results of a numerical model coded in Fortran. This numerical model uses a doubling-adding radiative transfer algorithm to simulate the polarisation properties of the designated atmospheric profile. The atmospheric profile consists of gas and aerosols, the latter modelled by spherical particles using Mie scattering theory. The numerical model results are processed and compared to the observations using a Matlab script. The particle properties are constrained by the observations using the wavelength filters, the implemented methane absorption and by using a variable cloud pressure and haze optical thickness. The numerical model results best matching the observations show higher altitude clouds in the higher polarisation degree regions known as the zones, and lower altitude clouds in the belts. The optical thickness of the haze layer turns out to be low or zero in the zones and higher in the belts. To better characterise Jupiter's atmospheric structure, several aspects relating to the observations and the numerical model have to be investigated in more detail in order to improve the matching of the two.

In this thesis, a new method to approximate the cost function of Low-Thrust, Multiple-Gravity-Assist interplanetary trajectories using a Machine Learning surrogate is proposed. This method speeds up the optimization process without fine tuning of the surrogate parameters for every individual case. The computational cost of obtaining training data was identified as the main limitation when using Machine Learning methods for this purpose. Therefore, the surrogate was built with an Online Sequential Extreme Learning Machine Multi-Agent System (OS-ELM-MAS) due to its theoretical good performance when the training data is limited. A high-fidelity global optimization problem was implemented, and a method to include the surrogate during the optimization process was designed. This method does not require specialized optimization algorithms. The parameters that control the interaction between the surrogate and the optimization process were identified and a procedure to obtain the best values was designed and applied. The final results show that the use of the surrogate improves the optimization results when evaluations of the cost function are computationally expensive. However, the values of the parameters that control the interaction between the surrogate and the optimization algorithm had to be carefully selected. The search for a general procedure to obtain these parameters without repeated tests is proposed for future research. Several applications to new optimization problems of the method developed in the thesis are also proposed for future research.

The Kuiper Belt is considered to be formed by remnants of the original Solar System, that is why exploration missions to that region are susceptible of having an enormous scientific impact. Nonetheless, it is far away from Earth, missions to KBO targets a significant challenge. Additionally, current methods to identify trajectories that encounter multiple KBOs are computationally intensive with impractically long run times on the order of months.

The present work deals with applying a rapid low-fidelity technique to identify candidate preliminary KBO sequences, to be used as a starting point for futuremission designers to identify trajectories tomultiple KBOs. This pathfinding approach uses two consecutive grid search types.

First, awell-tuned grid search is implemented using Lambert arcs to reach a first KBO, including the introduction of a new, systematic approach to identify the step sizes in target-body arrival date for the Lambert-based grid search. Then, second and third KBO encounters are assessed from the results of the first grid search and second KBO search respectively. Both second and third KBO searches are performed with a new algorithm consisting of a time grid along with STM linear propagation for maneuver calculation. Finally, an example trajectory resulting from this technique that encounters two KBOs is given as a potential flyable route.

CryoSat-2 is a European Space Agency (ESA) altimeter mission with an objective to study the connection between cryosphere melting and global sea level rise. The satellite carries a Doppler navigation system (DORIS) and a Satellite Laser Ranging system (SLR) to aid the precise computation of orbits down to centimetre level.
CNES/IDS releases DORIS tracking data in two formats for CryoSat-2. One is the raw format called RINEX and other is the pre-processed Doppler format called version 2.2. V2.2 data contains all information necessary for straightforward usage in orbit determination - measurements time-tagged in TAI, range-rate measurements, ionospheric correction, tropospheric correction, antenna corrections and flags that indicate unusable measurements. RINEX does not contain any corrections and has the phase and pseudorange measurements at short latency allowing users to have flexibility in processing. Additionally, data required for formulating the corrections are present in RINEX. For missions in and after 2016, CNES/IDS supplies tracking data only in RINEX and not in V2.2. Analysis centres using DORIS data now have to independently develop processing strategies to process RINEX data. This problem is the main objective of this research. In this thesis, a pre-processor called RX2RR (RINEX to Range-Rate) has been built in Fortran in an attempt to process the raw data and compute all the necessary corrections. RX2RR converts RINEX format to a format exactly similar to V2.2 such that RINEX can now be used in any orbit determination tool that has been previously using V2.2. In this processor, clock synchronisation of on-board clock to International Atomic Time is performed. A new approach of utilizing Meteorological data in RINEX for troposphere delay corrections is implemented. Use of real time data from numerical weather models is also presented for tropospheric correction. Ionospheric delay and antenna phase centre corrections are performed using iono-free phase centre. An editing strategy to remove outliers in Doppler data is implemented and tested. To demonstrate the performance of the tool, we perform orbit determination using NASA Goddard Space Flight Center’s orbit computation software GEODYN-II. We use RX2RR processed RINEX data and CNES processed V2.2 data of CryoSat-2 for year 2016. Tracking residuals from both POD runs are compared and average difference in R.M.S residual is found to be approximately 0.011 mm/s over a year. This validates that the corrections are formulated and implemented correctly. The result proves our capability to process the RINEX measurements independently and the tool developed has extended the capability of GEODYN-II to process RINEX observations from DORIS system.

In interplanetary mission design, ballistic capture is the phenomenon by which a spacecraft approaches its target body, and performs a number of revolutions around it, without requiring manoeuvres in between. For a spacecraft to be captured, its gravitational interaction with at least two celestial bodies has to be taken into account. Because of their fail-safe nature (eliminating the possibility of single point failures), their fuel efficiency and their wider launch windows, ballistic capture trajectories are of particular scientific and engineering interest. Capture orbits are characterized by a specific qualitative dynamics, defining almost-invariant regions in a given space, guiding transport phenomena; the introduction of structures, defining and bounding such domains, naturally follows. Traditionally, the set of initial conditions leading to capture, the Capture Set, has been computed by sampling the domain of interest, and hence analysing the forward and backward behaviour of the orbit associated to each sample. The main limitations of this approach reside in its large computational cost and, even for a dense grid, in the non-smooth approximation of the aforementioned boundary regions; the theory of Lagrangian Coherent Structures (LCS) has the potential of overcoming both limitations, allowing at the same time for a more insightful description of the phenomenon. In fact, Lagrangian Coherent Structures identify transport barriers in dynamical systems, separating regions with qualitatively different dynamics. The development of heuristics applicable to ballistic capture trajectory design and informed by such theory (i.e. flow-informed) appears desirable. In this research, different flow-informed approaches are presented and their relations with ballistic capture are discussed: following, a new heuristic, the Stroboscopic Strainline, is introduced. This new tool is therefore applied to different case studies at Mars, in order to approximate the capture sets associated to different numbers of revolutions and geometries. While a real-ephemerides model has been used to model the dynamical environments, different levels of fidelity have been investigated: perturbing forces have been introduced not only to obtain more accurate results, but also to test the robustness of the proposed technique with respect to different features of the underlying dynamical model. Finally, it is shown how Stroboscopic Strainlines are a good candidate for characterizing the qualitative behaviour of ballistic trajectories, both forward and backward in time.

Building on recent advances in the fields of low-thrust trajectory optimization based on shaping methods, Artificial Neural Networks, and surrogate models in Evolutionary Algorithms, an investigation into a novel optimization routine is conducted. A flexible Python tool to evaluate linked trajectories in a two-body model based on the hodographic shaping method is implemented and used to develop an evolutionary optimization approach where a Genetic Algorithm is assisted in finding new candidate solutions by a surrogate model. This surrogate is constructed from previous fitness function evaluations using Machine Learning, specifically by training an Artificial Neural Network. After deriving suitable (hyper-)parameters for the Genetic Algorithm and the Artificial Neural Network an experimental investigation into the algorithm's performance is conducted with a focus on the design of the surrogate for low-thrust trajectory problems. Two example problems based on the Dawn trajectory and the GTOC2 problem are studied. The surrogate approach is able to find good new candidate solutions, i.e. solutions that improve the population's overall fitness, especially when the surrogate is designed to approximate the shaping computation. Additionally, the use of a surrogate pretrained on a general data set of low-thrust transfers is tested and found to considerably improve the initial quality of the model, meaning that more good candidate solutions are found early on, accelerating the algorithm's convergence.

Bottom-up thermal-mechanical design and analysis of a deployable baffle, which serves as a deployable thermal control system for the Deployable Space Telescope. Research being conducted on how to create a stable thermal environment for the mirror support structures so that in-orbit thermo-elastic drift budgets will be met, as well as designing and analysing a feasible deployment system.

Given the difficulty that is normally associated with tuning highly nonlinear control systems, such as seen in LEO spacecraft, it is interesting to evaluate how new controller types perform. The measured data from the GOCE mission has led to the creation of high fidelity torque models describing the angular perturbations acting on a spacecraft. These torque models present an excellent opportunity to test the performance of new magnetically actuated attitude control methods. The work done in this thesis used these torque models in a simulation environment to evaluate the performance of an INDI-based control architecture for controlling the attitude of a GOCE-type spacecraft, using magnetic control actuation only. The goal was to evaluate whether an INDI-based control architecture can meet the same requirements that were set for the GOCE mission, and simultaneously evaluate the difficulty of tuning the controller and its sensitivity to errors and changes in gains once it is tuned. To achieve this a PD-controller was used as a reference controller, and two INDI-based controllers were set-up. One with a linear control outer loop (LINDI), and one with an NDI outer loop (NINDI). All three controllers have been tuned using a genetic algorithm.

With the introduction of Interplanetary Laser Ranging (ILR), the acquired tracking measurements accuracy of planets can be improved drastically (up to a few millimeters) which can result in an improvement in planetary ephemerides of not only the planet which is the target of laser ranging but also other bodies in the solar system due to dynamical coupling between the bodies. A quantitative analysis is performed to analyze how much improvement in the current planetary ephemerides can be achieved if highly accurate laser ranging observation were to be introduced in the current planetary ephemerides generation processes. The thesis achieved this by developing an ephemerides generation model using TU Delft's Astrodynamic Toolkit (i.e TUDAT) in which planetary ephemerides are generated for two cases. Once using simulated laser ranging observations to Mars between 2020 and 2023 and once without utilizing laser ranging observations. By comparing the estimated planetary ephemerides of the two cases, it is concluded that laser ranging to Mars resulted in a more stable and close to a factor of two improvement in ephemerides uncertainty for most of planets. The ephemerides of the Mars itself sees nearly a factor of ten improvement in uncertainty which resulted in a significant improvement in the knowledge of asteroid masses. The estimated mass parameter of 11 of the most perturbing asteroids in the solar system see more than a factor of ten improvement in their uncertainty which is unprecedented. Laser ranging to Mars and its cascade effect on the orbit of Mercury resulted in providing better constraints on PPN parameter γ and Sun's oblateness parameter J₂ allowing γ to be determined with an uncertainty of 5.5 x 10^-8 which is 3 order of magnitude better than the constraints provided from Cassini experiment. An order of magnitude improvement is also observed is Sun's J₂ parameter estimating it to an uncertainty level of 2.0 x 10^-9.

Measurements in the frequency range below 30 MHz, key to a better understanding of the origins of our universe, are one of the last unexplored areas of radio astronomy. Low frequency measurements suffer greatly from disturbance from man-made signals. Therefore, satellite missions are proposed which use the Moon as a shield from these disturbances, by making use of the Earth-Moon L2 Lagrange point. Such missions require large numbers of small satellites. One of the challenges for these missions is getting the satellites into their destination orbit with a very small Delta V budget. This research looks into the use of low energy trajectories for such a mission transfer trajectory.
Low energy trajectories are found on the invariant manifolds of the CR3BP and may be classified into several categories. Different combinations of these categories lead to different types of transfer trajectories. Four possible combinations were considered in this research, and compared to see which one best suits a small satellite mission to the Earth-Moon L2 Lagrange point. One combination has been previously researched in literature, the other three are new options for a transfer to the Earth-Moon L2.
The approach known from literature resulted in transfers with a required Delta V of down to 28 m/s. Using one of the other approaches, this could be reduced to 9 m/s. Additionally, one of the approaches allows for a station-keeping orbit around the Sun-Earth L2 point, which does not only make scheduling of the transfer easier, but also allows for additional mission objectives. These are encouraging results, showing that possibilities exist for the use of low energy trajectories for a lunar L2 mission.