<p>Multiple Signals of Opportunity (multi-SoOp) across different frequencies and polarizations</p> <p>offer a potential breakthrough for remote sensing of root-zone soil moisture (RZSM). Deeper penetration depths of existing communication transmissions in the frequency ranges of 137–138, 240–270, and 360–380 MHz enable the estimation of RZSM by complementing global navigation satellite system reflectometry (GNSS-R) in L-band. The small form factor of the multi-SoOp observatory allows for high spatiotemporal coverage of RSZM by a satellite constellation in a cost-effective manner. This study aims to develop models and tools to define mission requirements for various system parameters that affect observation accuracy and coverage, for the advancement of spaceborne multi-SoOp remote sensing. These parameters include frequency and polarization combinations, observation error, inter-frequency temporal coincidence, and configuration of the satellite constellation. We present the development of a retrieval algorithm and the sensitivity analysis of retrieval accuracy. The retrieval algorithm was evaluated using synthetic observations generated from multiyear time series of in-situ soil moisture (SM) and satellite-based vegetation data. The combined use of both high and low frequencies improves retrieval accuracy by limiting uncertainties from vegetation and surface SM and providing sensitivity to deeper layers. A bivariate model, derived from the sensitivity analysis, facilitates error prediction for future science missions. We introduce a framework for tradespace exploration of the multi-SoOp satellite constellation. A constellation design study indicates that a Walker constellation comprising 24 satellites with 3 orbital planes at 500 km and 50° inclination optimizes the coverage and mission cost under mission requirements. A tower-based field experiment validated the performance of a prototype antenna for multi-SoOp using the interference pattern technique. More field experiments with improved instruments are required to further advance the multi-SoOp technique.</p>

Events such as forest fires or floods are a danger to our Earth’s environment and the people living in it. The sooner they can be detected, the less damage they can cause. An idea arises: use satellites to monitor the Earth and relay information to prevention and rescue organizations in a very short time, regardless of accessibility from ground. PandionAI is a Swedish start-up that aims to create a constellation of satellites that will carry built-in machine learning models that analyze the Earth images and detect early on such environmental catastrophes. The aim of this thesis is to design a constellation for such purpose. In parallel, a target list that includes potential places of interest for such events will be developed and the constellation performance will be evaluated with it by defining Key Performance Indicators (KPIs). The target list has a dynamic nature as weather changes and climate evolves, so events of interest will be at different places in the globe as time passes. Because of this, four different target lists were developed, one per season. The events covered by the target lists are the environmental hazards: fires, floods, deforestation and CO2 footprint from factories. Constellation design is a highly complex problem due to its infinite possible solutions for a given purpose. Nevertheless, one can optimize for specific design parameters and assumptions. This thesis proposes a model in which for a given number of total satellites, multiple constellations are compared, and the search for the optimal design is performed given the defined KPIs. Constellations in the optimization process are designed applying the 2-D Lattice Flower Constellation method and adding the twin satellite concept. / Händelser som skogsbränder eller översvämningar är en fara för vår jords miljö och människorna som lever i den. Ju tidigare de kan upptäckas, desto mindre skada kan de orsaka. En idé uppstår: att använda satelliter för att övervaka jorden och vidarebefordra information till förebyggande och räddningsorganisationer på mycket kort tid, oavsett tillgänglighet från marken. PandionAI är en svensk start-up som vars mål är att skapa en konstellation av satelliter som ska bära inbyggda maskininlärningsmodeller som analyserar analyserar satelliters bilder bilder och tidigt upptäcker sådana miljökatastrofer. Syftet med denna uppsats är att utforma en konstellation för detta ändamål. Parallellt kommer en mållista som inkluderar potentiella platser av intresse för sådana händelser att utvecklas och konstellationens prestanda kommer att utvärderas med den genom att definiera Key Performance Indicator-parametrar (KPI). Mållistan har en dynamisk karaktär, eftersom väder och klimat varierar över året säsonger och händelser, så händelser av intresse kommer att finnas på olika platser i världen med tiden. På grund av detta utvecklades fyra olika mållistor, en per säsong. De händelser som omfattas av mållistorna är miljöriskerna: bränder, översvämningar, avskogning och CO2 fotavtryck från fabriker. Konstellationsdesign är ett mycket komplext problem på grund av dess oändliga många möjliga lösningar för ett givet syfte. Ändå kan man optimera för specifika designparametrar och antaganden. Denna studie syftar till att förslå en modell för ett totalt givet antal satelliter, där flera konstellationer jämförs och finna den optimala designen givet KPIerna. Konstellationer i optimeringsprocessen är designade med tillämpning av 2D Lattice Flower Constellation-metoden och användning av tvilling-satellit-konceptet till tvillingsatellitkonceptet.

With increasing world tensions and improvements of satellites and their sensors, the interest and possibility of using space and satellites for defensive purposes has increased greatly. However, not much research has been conducted into the needs and possibilities of satellite constellations over Sweden, especially using SAR and optical sensors combined with AI object detection. This thesis provides insight in to the needs and requirements to achieve certain coverage and gap times and explores different constellation design methods to do so. This is done by combining large scale tests performed with genetic algorithm and a dual-axis propagator with theoretical and analytical methods. Results show that for micro-satellites under 100 kg based on current commercial technology, it is found that between 24 to 63 satellites are needed for 1 hour gap times depending on what combination of SAR and optical satellites are used. The genetic algorithm was found to not generate optimal constellations as the number of satellites increased beyond 12. It was however useful in mapping out possibilities and finding certain optimal parameters such as the inclination. The dual-axis propagator tested for its low processing load was found to be good for coverage analysis and estimating the shapes of the orbits. It was noted to have large positional errors however, limiting its use to analysis and not full constellation design. / Med ökande världsspänningar och förbättringar av satelliter och deras sensorer har intresset och möjligheterna att använda rymden och satelliter för försvarssyften ökat avsevärt. Dock har inte mycket forskning gjorts om behoven och möjligheterna med satellitkonstellationer över Sverige, särskilt när det gäller användningen av SAR och optiska sensorer i kombination med AI-objektdetektering. Denna avhandling ger insikt i behoven och kraven för att uppnå viss täckning och tidsgap samt utforskar olika metoder för konstellationsdesign för att uppnå detta. Detta görs genom att kombinera storskaliga tester med genetiska algoritmer och en dual-axis propagator med teoretiska och analytiska metoder. Resultaten visar att för mikrosatelliter under 100 kg, baserat på nuvarande kommersiell teknik, krävs mellan 24 och 63 satelliter för att uppnå gapptider på 1 timme, beroende på vilken kombination av SAR- och optiska satelliter som används. Det konstaterades att genetiska algoritmen inte tillförlitligt kunde hitta optimala konstellationer när antalet satelliter ökade bortom 12 st. Dualaxelpropagatorn, som testades för sin låga processbelastning, ansågs vara bra för täckningsanalys och uppskattning av omloppsbanornas former. Den hade dock stora positionsfel, vilket begränsade dess användning till analys och inte fullständig konstellationsdesign.

<p dir="ltr">The recent and upcoming increase in spaceflight missions to the lunar vicinity necessitates methodologies to enable operations beyond the Earth. In particular, there is a pressing need for a Space Domain Awareness (SDA) and Space Situational Awareness (SSA) architecture that encompasses the realm of space beyond the sub-geosynchronous region to sustain humanity's long-term presence in that region. Naturally, the large distances in the cislunar domain restrict access rapid and economical access from the Earth. In addition, due to the long ranges and inconsistent visibility, the volume contained within the orbit of the Moon is inadequately observed from Earth-based instruments. As such, space-based assets to supplement ground-based infrastructure are required. The need for space-based assets to support a sustained presence is further complicated by the challenging dynamics that manifest in cislunar space. Multi-body dynamical models are necessary to sufficiently model and predict the motion of any objects that operate in the space between the Earth and the Moon. The current work seeks to address these challenges in dynamical modeling and cislunar accessibility via the exploration of resonant orbits. These types of orbits, that are commensurate with the lunar sidereal period, are constructed in the Earth-Moon Circular Restricted Three-Body Problem (CR3BP) and validated in the Higher-Fidelity Ephemeris Model (HFEM). The expansive geometries and energy options supplied by the orbits are favorable for achieving recurring access between the Earth and the lunar vicinity. Sample orbits in prograde resonance are explored to accommodate circumlunar access from underlying cislunar orbit structures via Poincaré mapping techniques. Orbits in retrograde resonance, due to their operational stability, are employed in the design of space-based observer constellations that naturally maintain their relative configuration over successive revolutions. </p><p dir="ltr"> Sidereal resonant orbits that are additionally commensurate with the lunar synodic period are identified. Such orbits, along with possessing geometries inherent to sidereal resonant behavior, exhibit periodic alignments with respect to the Sun in the Earth-Moon rotating frame. This characteristic renders the orbits suitable for hosting space-based sensors that, in addition to naturally avoiding eclipses, maintain visual custody of targets in the cislunar domain. For orbits that are not eclipse-favorable, a penumbra-avoidance path constraint is implemented to compute baseline trajectories that avoid Earth and Moon eclipse events. Constellations of observers in both sidereal and sidereal-synodic resonant orbits are designed for cislunar SSA applications. Sample trajectories are assessed for the visibility of various targets in the cislunar volume, and connectivity relative to zones of interest in Earth-Moon plane. The sample constellations and observer trajectories demonstrate the utility of resonant orbits for various applications to sustain operations in cislunar space. </p>