The objective of this project is the development of a mission analysis tool for the nanosatellite company GomSpace Sweden. Although there are many existing software, they can be quite complicated and time consuming to use. The goal of this work is to build a simple app to be used at the earliest stages of space missions in order to obtain key figures of merit quickly and easily. By comparing results, assessing the feasibility of customer needs, analysing how various parameters affect each other, it enables immediate deeper understanding of the implications of the main design decisions that are taken at the very beginning of a mission. The tool shall aid the system engineering process of determining orbit manoeuvre capability specifically for CubeSat electric propulsion systems taking into account the most relevant factors for perturbation in Low Earth Orbit (LEO), i.e. atmospheric drag and Earth’s oblateness effects. The manoeuvres investigated are: orbit raising from an insert orbit to an operating orbit, orbit maintenance, deorbiting within the space debris mitigation guidelines and collision avoidance within the 12 to 24 hours that the system has to react. The manoeuvres cost is assessed in terms of Delta v requirements, propellant mass and transfer times. The tool was developed with MATLAB and packaged as a standalone Linux application. / Målet med detta examensarbete var att utveckla ett verktyg för missionsanalys för nanosatellitföretaget GomSpace Sweden. Det finns många andra mjukvaror för att nå samma mål men de är ofta komplicerade och tidskrävande. Det specifika målet var således att skapa en enkel applikation som kan användas i de tidiga stegen av utformning av rymduppdrag för att snabbt och enkelt få fram viktiga parametrar. Genom att jämföra resultat, uppskatta genomförbarheten av kundbehov och analysera hur olika parametrar påverkar varandra kan omedelbar förståelse erhållas rörande påverkan av designbeslut som tas i början av rymduppdragen. Verktyget ska stödja systemingenjörsprocessen genom att uppskatta banförflyttningskapacitet för elektriska framdrivningssystem för CubeSats och ta i beaktande de mest relevanta faktorerna gällande störningar i låg jordbana (LEO), i.e. atmosfäriskt motstånd och effekterna av Jordens form. De undersökta manövrarna är: banhöjning från injektionsbana till operationell bana, banunderhåll, bansänkning som följer riktlinjerna för rymdskrot och kollisionsundvikande inom de 12 till 24 timmar som systemet har på sig att reagera. Kostnaden för manövrarna är uppskattade genom DeltaV-krav, massan av bränslet och förflyttningstider. Verktyget utvecklades med MATLAB och paketerades som en fristående applikation i Linux.

3D bioprinting has developed tremendously in the last couple of years and enables the fabrication of simple, as well as complex, tissue models. The international space agencies have recognized the unique opportunities of these technologies for manufacturing cell and tissue models for basic research in space, in particular for investigating the effects of microgravity and cosmic radiation on different types of human tissues. In addition, bioprinting is capable of producing clinically applicable tissue grafts, and its implementation in space therefore can support the autonomous medical treatment options for astronauts in future long term and far-distant space missions. The article discusses opportunities but also challenges of operating different types of bioprinters under space conditions, mainly in microgravity. While some process steps, most of which involving the handling of liquids, are challenging under microgravity, this environment can help overcome problems such as cell sedimentation in low viscous bioinks. Hopefully, this publication will motivate more researchers to engage in the topic, with publicly available bioprinting opportunities becoming available at the International Space Station (ISS) in the imminent future.

Navigation is integral to modern infrastructure, with GPS serving as the foundation for applications in transportation, banking, and communications. Despite its widespread success, GPS is vulnerable to failures due to its low received signal power, susceptibility to jamming, and reduced accuracy in dense urban environments and deep fades. A failure of GPS could have severe consequences, making it crucial to explore alternative or supplementary navigation technologies. This work investigates the potential of three approaches—low Earth orbit (LEO) satellites, reconfigurable intelligent surfaces (RISs), and near-field propagation—to enhance localization accuracy and resilience. LEO satellites, originally designed for communication, have recently seen widespread deployment through constellations such as Starlink, OneWeb, and Kuiper. Their growing presence presents an opportunity to explore their feasibility for 9D localization, which includes 3D position, velocity, and orientation estimation. However, using LEO satellites for localization introduces significant challenges, including ionospheric delays, high Doppler shifts, limited synchronization due to the absence of atomic clocks, and uncertainty in satellite ephemeris data. To address these challenges, we leverage estimation theory and the Fisher Information Matrix (FIM) to establish theoretical bounds on localization performance. Our analysis shows that localization is possible using signals from multiple LEO satellites observed across several time slots, even in the presence of time and frequency offsets. We derive closed-form expressions for the FIM and identify conditions under which localization is feasible, highlighting the required number of satellites, base stations, and transmission slots. RISs provide another avenue for enhancing localization by dynamically shaping wireless propagation channels through software-controlled meta-material surfaces. We analyze the localization potential of RISs under both near-field and far-field conditions, focusing on angle of incidence, reflection, and orientation estimation. Our FIM-based study reveals that in far-field scenarios, angle estimation is only feasible with multiple RIS phase profiles, whereas in near-field, a single phase profile suffices. This distinction has implications for RIS-aided positioning, indicating that a single RIS reflection may not provide sufficient information for localizing a user in the far-field unless additional mechanisms, such as multiple reflections or phase variations, are employed. We further investigate near-field propagation, assessing the available localization information when a source transmits to a destination node. Our Fisher information analysis reveals that in the near-field regime, 3D orientation and position can be jointly estimated, whereas in the far-field, only 2D orientation and position can be determined. Additionally, we explore the impact of propagation model mismatches on direction-of-arrival (DOA) estimation using the MUSIC algorithm. Our simulations quantify the performance degradation when incorrect assumptions are made about the propagation environment, showing that estimation accuracy suffers significantly when near-field effects are ignored. Notably, in near-field scenarios, using a far-field-based beamforming model leads to an underestimation of DOA estimation errors, while in the far-field, MUSIC remains effective with appropriate beamforming design. Overall, our findings indicate that LEO satellites, RISs, and near-field propagation hold significant potential for overcoming the limitations of GPS and enabling precise localization for next-generation applications. By leveraging these technologies, it may be possible to achieve robust navigation in environments where GPS performance is compromised, paving the way for resilient and high-accuracy positioning solutions. / Doctor of Philosophy / Navigation is so ubiquitous that we spend little time thinking about its inner workings. The Global positioning system (GPS) works so well that navigation for airplanes and cars relies heavily on it. Moreover, on the less-known side, the use of GPS in the banking sector is a little-known, but vitally important use-case as banking institutions utilize GPS to provide strict timing to synchronize all their clocks. Considering these, a GPS failure would be catastrophic, costing millions and possibly resulting in a humongous loss of life. Hence, it is essential to address the scenarios where GPS can fail. The main challenge that GPS faces is the low received power of its signal. It is well known that the received signal power of GPS signals is similar to viewing a light bulb from a distance of 1 km. This dramatically increases the possibility of the signal being jammed. Also, it can become unreliable in deep fades and urban canyons since the signal is received well below the noise floor. Due to these concerns, there is a need to provide a backup to replace or, at the very least, augment GPS. Three technologies that could enable navigation are reconfigurable intelligent surfaces (RISs), near-field signal processing, and low Earth orbit (LEO) satellites. Interest in LEO satellites has skyrocketed due to the launch of several new constellations - Boeing, SpaceMobile, OneWeb, Telesat, Kuiper, and Starlink as well as the deployment of satellites into existing constellations - Orbcomm, Iridium, and Globalstar. Although these LEO satellites are being deployed for communication purposes, their ubiquitous deployments mandate a rigorous investigation of the utility of these satellites to provide 9D localization (3D positioning, 3D velocity estimation, and 3D orientation estimation) of a terrestrial re- ceiver. We utilize estimation theory to show that with sufficient spacing between time slots and in the presence of time and frequency offsets and Doppler rate, it is possible to perform 9D localization (3D position, 3D velocity, and 3D orientation estimation) of a receiver by utilizing the signals from three LEO satellites observed during three transmission time slots received through multiple receive antennas. RISs are envisioned as planar surfaces comprising sub-wavelength-sized meta-materials ca- pable of controlling a wireless propagation channel by applying a desired transformation on the incoming signal through the software control of each meta-material, and this unique ability to control the harsh wireless channel has led to many works investigating the suit- ability of RISs for localization. We show under certain conditions that we can estimate the angles of incidence, reflection, and the orientation offset at the RIS and utilize these angles for localization. We also investigate the available information during near-field propagation under the case of a downlink source transmitting to a destination node and show that the near-field provides additional information for localization. Our work indicates that the RISs, LEO satellites, and near-field propagation could be used to achieve the accuracy needed for futuristic localization use cases.

<p>Our modern society is more dependent on its assets in space now more than ever. For<br> example, the Global Positioning System (GPS) many rely on for navigation uses data from a<br> 24-satellite constellation. Additionally, our current infrastructure for gas pumps, cell phones,<br> ATMs, traffic lights, weather data, etc. all depend on satellite data from various constel-<br> lations. As a result, it is increasingly necessary to accurately track and predict the space<br> domain. In this thesis, after discussing how space object tracking and object position pre-<br> diction is currently being done, I propose a machine learning-based approach to improving<br> the space object position prediction over the standard SGP4 method, which is limited in<br> prediction accuracy time to about 24 hours. Using this approach, we are able to show that<br> meaningful improvements over the standard SGP4 model can be achieved using a machine<br> learning model built based on a type of recurrent neural network called a long short term<br> memory model (LSTM). I also provide distance predictions for 4 different space objects over<br> time frames of 15 and 30 days. Future work in this area is likely to include extending and<br> validating this approach on additional satellites to construct a more general model, testing a<br> wider range of models to determine limits on accuracy across a broad range of time horizons,<br> and proposing similar methods less dependent on antiquated data formats like the TLE.</p>

<p>    </p> <p>Additive manufacturing (or 3D printing) is one of the manufacturing processes which is currently being explored for its applicability under space boundary conditions, also known as in-space manufacturing. The space boundary conditions specifically affect material properties which in turn affect the printability of materials in space. Printing of soft materials in space is a novel application and the intent of this research was to print the softest of materials: edible materials, as a case study. 3D food printing is a novel food delivery method of using food products to either reproduce as a more aesthetically pleasing product or to print more nutrient-diverse foods. Launch of payload carrier and the boundary conditions of low Earth orbit including a vacuum environment, microgravity, temperature fluctuations, etc. These conditions make printing difficult, and my thesis is to overcome the boundary conditions (except microgravity) using a 3D soft material printer operating within a CubeSat. A CubeSat is a small satellite usually launched as an auxiliary payload used for basic Earth observation and radio communication. The printer must be able to survive launch and operation conditions, print within a simulated space environment, and adhere to the American Society for Testing and Materials (ASTM) specific definition of additive manufacturing. The 3D soft material printer was designed, fabricated, and tested using space and CubeSat boundary conditions for determining optimal design. Testing conditions including: (1) printing under Earth conditions showing it follows ASTM standards, (2) surviving NASA standards for vibration testing for microsatellites under launch conditions, (3) completing a print under a vacuum setting. The results of the testing would prove a small microsatellite could print in the vacuum of space and survive launch parameters. Further work would provide insight into the design of food printers being readily available in smaller sizes and its operability in microgravity condition. </p>