Satellite Research Articles

Multi-perspective analysis of sustainability metrics characterising the debris environment

To assess the effectiveness of mitigation measures, long-term simulations of the debris environment are often analysed and evaluated using simple metrics such as the total number of objects or the frequency of fragmentation events. In addition, more complex criticality metrics have been developed in the past to rank objects according to their environmental impact and evaluate the overall state of the debris environment. In this context, three different perspectives are particularly worth highlighting: object-specific metrics that characterise the criticality of individual objects and orbits, spatial metrics that can be used to identify particularly vulnerable orbital regions, and global metrics which describe the sustainability of the environment as a whole. Typically, the criticality metrics are specific to one of the respective perspectives, but unification across and convertibility between perspectives would allow for a more comprehensive assessment of sustainability. In this context, a methodology is developed to transform object-specific and spatial metrics into one another. The conversion concept enables a comparison of two structurally different metrics from their respective initial object-specific and spatial domain. Furthermore, the third perspective is taken into account by using different aggregation methods to retrieve a global metric from the initial object-specific and spatial description. The three perspectives then are compared by conducting environment evolution simulations for various baseline scenarios using a common space debris population in low Earth orbit. The comparative analysis identifies commonalities and differences of the chosen metrics in the three different perspectives and how the conversion between them affects their quantification of sustainability. The multi-perspective convertibility and aggregation of single-perspective metrics represents a contribution to the generalisation of sustainability metrics for different scopes of application.

Info-Geometric Analysis of Gamma Distribution Manifold with Gamma Distribution Impact to Advance Satellite Earth Observations

This study aims to reveal the revolutionary Gamma Distribution Manifold (GDM) info-geometric analysis combined with potential Gamma distribution (GD) applications to advance Satellite Earth Observations (SEOs). An exposition of the GDM Fisher Information Matrix (FIM) was undertaken, together with the analytic investigation of the existence of FIM’s inverse. The derivation of GDM’s Geodesic Equations (GEs) is undertaken. The solution of the obtained Geodesic Equations is optimally complicated, and it provides more extensions to numerous open problems. Notably, the current paper provides a first-time unification between three multi-interdisciplinary fields, namely, information geometry theory, probability theory, and Satellite earth observations. Looking at the other side of the coin, the provided revolutionary approach in this current work reports the significant impact of info-geometric analysis on the probabilistic dynamics as well as the influential role of information geometry in the satellite and space industry. This poses numerous open issues that initiate a new form of contemporary unification between these inter-disciplinaries to discover another visionary thinking out of traditional statistical frames. In other words, refraining ourselves from using classical statistical frames of thinking and delving into a new info-geometric vision of statistical distributions as well as examining real-life applications of information geometry to advance satellite earth observations. The curtain is drawn on this paper by providing several challenging open problems in combination with a concluding remark and the next phase of research.

The Thermo-Mechanical Properties of Carbon-Fiber-Reinforced Polymer Composites Exposed to a Low Earth Orbit Environment

In this study, we focus on 3D-printed PEEK/CFRTP (Carbon-Fiber-Reinforced Thermoplastic) and PEEK (Polyether Ether Ketone) materials as new space materials. In space, there are intense ultraviolet (UV) rays that are weakened by the atmosphere on Earth, so it is essential to understand the degradation of materials due to UV rays in advance. Therefore, we developed a materials science experiment called the Material Mission, which will be carried out on board Ten-Koh 2. This mission measures the coefficient of thermal expansion (CTE) of the CFRTP samples and the PEEK samples in LEO without recovery. So, we developed a thermal expansion observation system to be installed on the Ten-Koh 2 satellite. In addition, UV irradiation tests simulating the UV environment in LEO were conducted as ground tests. From the results of the ground tests, it was possible to determine in advance the degree of degradation of each material in the UV environment, even up to 100 ESD. By utilizing these results in mission operations, more meaningful measurement results can be obtained, and this mission development can contribute greatly to developing new space materials in the future.

Space Debris Capture - About New Methods of Tethered Space Net Opening by Tubular Booms

Abstract Nowadays, space debris is one of the main subjects of discussion regarding satellites in Earth's orbit. Right now, there are about 26,000 orbiting satellites and only few of these satellites are operational. Recently, the Polish space sector has been strongly growing and delivering instruments working in space. The first part of this paper describes the several space instruments designed in the Space Research Centre Polish Academy of Science (SRC PAS). Instruments such as SWI, RPPWI, LPPWI, Ebox or Pre-boxes have been created for a mission to Jupiter named “JUICE”. After fulfilling their scientific mission, these instruments can increase the amount of debris in space. This is one of the reasons for taking up the topic of space debris reduction and the use of technical solutions used in this mission for the proposed solution presented later. The second part of this paper describes the new methods related to space debris. The activities can be related to the space debris removal programmes. The paper describes two methods developed by Polish scientists used for removal of space debris. One of them is the new capture method and mechanism designed for it. The special mechanism is based on tubular boom application for opening the net, to capture the space debris. The main parts of the mechanism are mechanisms which have been used in the JUICE space mission. The paper describes the main idea for these new methods, and for the design part prepared the strength confirmation by structural analysis. The main function of the mechanism has been verified by simulations and tests performed in laboratories.

Comparison of the SRP spherical model between LEO and GEO satellites

Solar Radiation Pressure (SRP) is a phenomenon caused by the pressure exerted by solar photons on a satellite’s surface when it is exposed to sunlight. It is a form of radiation force and can significantly impact the motion and behaviour of satellites in space. SRP influences a satellite’s orbit by causing changes in its semimajor axis, eccentricity, inclination, argument of perigee, right ascension of the ascending node, and mean anomaly. SRP models are used to simulate the effects of solar radiation pressure on satellites. These models are essential for accurately predicting satellite trajectories and orbital behaviour. There are several types of SRP models, such as spherical model, flat model, box-wing model, faceted model, and analytical SRP models. This research focuses on Telkom 1 and LAPAN A1 satellites, both belonging to Indonesia and positioned in Geostationary Earth Orbit (GEO) and Low Earth Orbit (LEO) orbits, respectively. The study aims to find a comparison of the effects of SRP spherical model on LEO and GEO satellites. Our modelling shows that the semimajor axis and eccentricity are sensitive to SRP, while the inclination and right ascension of the ascending node are not significantly affected. Comparing the effects of SRP on LEO and GEO satellites, we concluded that both LEO and GEO orbit experience the most significant fluctuations in January (perihelion), likely due to the influence of solar radiation pressure.

On the Mesoscale Structure of Coronal Mass Ejections at Mercury’s Orbit: BepiColombo and Parker Solar Probe Observations

On 2022 February 15, an impressive filament eruption was observed off the solar eastern limb from three remote-sensing viewpoints, namely, Earth, STEREO-A, and Solar Orbiter. In addition to representing the most-distant observed filament at extreme ultraviolet wavelengths—captured by Solar Orbiter's field of view extending to above 6 R ⊙—this event was also associated with the release of a fast (∼2200 km s−1) coronal mass ejection (CME) that was directed toward BepiColombo and Parker Solar Probe. These two probes were separated by 2° in latitude, 4° in longitude, and 0.03 au in radial distance around the time of the CME-driven shock arrival in situ. The relative proximity of the two probes to each other and the Sun (∼0.35 au) allows us to study the mesoscale structure of CMEs at Mercury's orbit for the first time. We analyze similarities and differences in the main CME-related structures measured at the two locations, namely, the interplanetary shock, the sheath region, and the magnetic ejecta. We find that, despite the separation between the two spacecraft being well within the typical uncertainties associated with determination of CME geometric parameters from remote-sensing observations, the two sets of in situ measurements display some profound differences that make understanding the overall 3D CME structure particularly challenging. Finally, we discuss our findings within the context of space weather at Mercury's distance and in terms of the need to investigate solar transients via spacecraft constellations with small separations, which has been gaining significant attention during recent years.

Future climate-induced distribution shifts in a sexually dimorphic key predator of the Southern Ocean.

The response to climate change in highly dimorphic species can be hindered by differences between sexes in habitat preferences and movement patterns. The Antarctic fur seal, Arctocephalus gazella, is the most abundant pinniped in the Southern Hemisphere, and one of the main consumers of Antarctic krill, Euphausia superba, in the Southern Ocean. However, the populations breeding in the Atlantic Southern Ocean are decreasing, partly due to global warming. Male and female Antarctic fur seals differ greatly in body size and foraging ecology, and little is known about their sex-specific responses to climate change. We used satellite tracking data and Earth System Models to predict changes in habitat suitability for male and female Antarctic fur seals from the Western Antarctic Peninsula under different climate change scenarios. Under the most extreme scenario (SSP5-8.5; global average temperature +4.4°C projected by 2100), suitable habitat patches will shift southward during the non-breeding season, leading to a minor overall habitat loss. The impact will be more pronounced for females than for males. The reduction of winter foraging grounds might decrease the survival of post-weaned females, reducing recruitment and jeopardizing population viability. During the breeding season, when males fast on land, suitable foraging grounds for females off the South Shetland Islands will remain largely unmodified, and new ones will emerge in the Bellingshausen Sea. As Antarctic fur seals are income breeders, the foraging grounds of females should be reasonably close to the breeding colony. As a result, the new suitable foraging grounds will be useful for females only if nearby beaches currently covered by sea ice emerge by the end of the century. Furthermore, the colonization of these new, ice-free breeding locations might be limited by strong female philopatry. These results should be considered when managing the fisheries of Antarctic krill in the Southern Ocean.

Machine Learning Implementation on TTV Analysis using TTVFast

Exoplanet research has undergone rapid development lately due to the increasing number of space telescopes and satellite surveys launched in recent years. Two missions with the most exoplanet discoveries using transit methods are Kepler and TESS missions. Both missions focused on photometric surveys to detect planets by observing the periodic dimming of a stars brightness as a planet passes in front of it. There is another method that could take advantage of transit observations called transit timing variation method. By observing the deviation of the transit time of transiting planet we could infer the existence of another body in the system. Performing exoplanet parameter estimation using TTV data is an extensive process. Estimating exoplanet parameters using TTV, we must fit the TTV data using a wide range of parameters using n-body simulation. N-body simulation in this scale is computationally costly. To estimate planet parameters, we need to run thousands of n-body simulations. With the increasing trend of using machine learning methods in the research process, we try to implement the machine learning method to make TTV analysis more effective and efficient. We implement the application of machine learning to n-body simulation using REBOUND and TTVFAST and compare the results. REBOUND is a Python-based library designed for simulating the dynamics of n-body systems, particularly celestial bodies like planets, stars, and other objects that interact gravitationally. While TTVFAST is a modified n-body simulation code that is specifically designed to calculate TTV on transiting planetary systems. We found that TTVFAST is much faster than REBOUND when generating samples for training and testing while still maintaining similar accuracy. Also, the machine learning model generated from both data samples is performed similarly.

Simulation and Design of Optimized Three-Layer Radiation Shielding to Protect Electronic Boards of Satellite Revolving in Geostationary Earth Orbit (GEO) Orbit against Proton Beams

The safety of electronic components used in aerospace systems against cosmic rays is one of the most important requirements in their design and construction (especially satellites). In this work, by calculating the dose caused by proton beams in geostationary Earth orbit (GEO) orbit using the MCNPX Monte Carlo code and the MULLASSIS code, the effect of different structures in the protection of cosmic rays has been evaluated. A multi-layer radiation shield composed of aluminum, water and polyethylene was designed and its performance was compared with shielding made of aluminum alone. The results show that the absorbed dose by the simulated protective layers has increased by 35.3% and 44.1% for two-layer (aluminum, polyethylene) and three-layer (aluminum, water, polyethylene) protection respectively, and it is effective in the protection of electronic components. In addition to that, by replacing the multi-layer shield instead of the conventional aluminum shield, the mass reduction percentage will be 38.88 and 39.69, respectively, for the two-layer and three-layer shield compared to the aluminum shield.

Systemic design of the very-high-resolution imaging payload of an optical remote sensing satellite for launch into the VLEO using an small launch vehicle

The very low Earth orbit (VLEO), which includes orbits with altitudes of 100–450 km, has distinct advantages for remote-sensing spacecraft. Lower altitudes allow payloads with smaller dimensions, weight, and power to achieve performances similar to or better than larger payloads in higher orbits in remote sensing and Earth observation missions. The most important advantage of low orbits for optical imaging systems is the higher resolution these payloads can attain. The present paper systemically designs the very high-resolution imaging payload of an optical remote sensing satellite for operations in the VLEO. The aim of this design is to achieve a high spatial resolution of the optical imaging platform and reach a 1-m ground sampling distance (GSD) as reported. Therefore, considering an orbital altitude of 300 km and system calculations, the implementation of this method is described. The results obtained show that the proposed platform (VHR4) has better diffraction-limited ground resolution compared to several examples of operational satellite platforms under approximately equal orbital conditions. Also, by calculating and estimating the weight, power, and dimensions of the proposed imaging platform (VHR4), it is shown that the platform meets the requirements of a small satellite launcher in terms of weight, dimensions, and power.

LabOSat-01: A Payload for In-Orbit Device Characterization

LabOSat is an applied research group whose main objective is to increase the Technology Readiness Level of electronic devices and systems for their use in satellite missions. Since 2013 the Group has participated in 9 Low Earth Orbit missions in collaboration with Satellogic. Its flagship payload, LabOSat-01, is a Source-Measurement-Unit instrument dedicated to the electrical characterization of electronic devices. In this brief communication, results of in-orbit operation of LabOSat-01 are presented. A summary of the Group activities in the period 2013-2022 is also presented. These results represent almost 10 years of experience in 9 missions hosting different technologies in orbit.

Carrying Capacity of Low Earth Orbit Computed Using Source-Sink Models

The low-Earth-orbit (LEO) environment will likely experience an exponential growth of the anthropogenic space object population, also due to the many proposed large constellations, which could negatively affect the sustainability of the space environment if no proper regulatory actions are introduced. This paper introduces a methodology to analyze high-capacity sustainable solutions of the LEO region from 200 to 900 km altitude. Sustainability is assessed through the stable equilibrium points of a source-sink model called MIT Orbital Capacity Assessment Tool 3 (MOCAT-3). Capacity is estimated using an optimization procedure that aims to compute the optimal launch rate that maximizes the number of satellites in LEO, subject to a risk-rate constraint. Results show that the sustainable number of satellites increases with the risk rate constraint. Moreover, the resilience of the proposed solutions is tested against a more accurate time-varying atmospheric density model and perturbations of the initial equilibrium population. The compatibility of the proposed solutions with future traffic launches and a strategy to accommodate future traffic needs are presented. Limitations of the current work are discussed, chiefly the importance of validation of model coefficients and behavior before resulting capacity estimates are used to guide actual decision-making.

Analyzing the robustness of LEO satellite networks based on two different attacks and load distribution methods.

Low earth orbit (LEO) satellite constellations have emerged as a promising architecture integrated with ground networks, which can offer high-speed Internet services to global users. However, the security challenges faced by satellite networks are increasing, with the potential for a few satellite failures to trigger cascading failures and network outages. Therefore, enhancing the robustness of the network in the face of cascading failures is of utmost importance. This paper aims to explore the robustness of LEO satellite networks when encountering cascading failures and then proposes a modeling method based on virtual nodes and load capacity. In addition, considering that the ground station layout and the number of connected satellites together determine the structure of the final LEO satellite network, we here propose an improved ground station establishment method that is more suitable for the current network model. Finally, the robustness of the LEO satellite networks is deeply studied under two different attacks and cost constraints. Simulations of LEO satellite networks with different topologies show that the maximum load attacks have a destructive impact on the network, which can be mitigated by adjusting the topology and parameters to ensure normal network operation. The current model and related results provide practical insights into the protection of LEO satellite networks, which can mitigate cascading risks and enhance the robustness of LEO systems.

The ideal wavelength for daylight free-space quantum key distribution

Quantum key distribution (QKD) has matured in recent years from laboratory proof-of-principle demonstrations to commercially available systems. One of the major bottlenecks is the limited communication distance in fiber networks due to the exponential signal damping. To bridge intercontinental distances, low Earth orbit satellites transmitting quantum signals over the atmosphere can be used. These free-space links, however, can only operate during the night, as the sunlight otherwise saturates the detectors used to measure the quantum states. For applying QKD in a global quantum internet with continuous availability and high data rates, operation during daylight is required. In this work, we model a satellite-to-ground quantum channel for different quantum light sources to identify the optimal wavelength for free-space QKD under ambient conditions. Daylight quantum communication is possible within the Fraunhofer lines or in the near-infrared spectrum, where the intrinsic background from the sun is comparably low. The highest annual secret key length considering the finite key effect is achievable at the Hα Fraunhofer line. More importantly, we provide the fundamental model that can be adapted, in general, to any other specific link scenario taking into account the required modifications. We also propose a true single-photon source based on a color center in hexagonal boron nitride coupled to a microresonator that can implement such a scheme. Our results can also be applied in roof-to-roof scenarios and are, therefore, relevant for near-future quantum networks.

Federated Learning in Satellite Constellations

Federated learning (FL) has recently emerged as a distributed machine learning paradigm for systems with limited and intermittent connectivity. This paper presents the new context brought to FL by satellite constellations, where the connectivity patterns are significantly different from the ones observed in conventional terrestrial FL. The focus is on large constellations in low Earth orbit (LEO), where each satellites participates in a data-driven FL task using a locally stored dataset. This scenario is motivated by the trend towards mega constellations of interconnected small satellites in LEO and the integration of artificial intelligence in satellites. We propose a classification of satellite FL based on the communication capabilities of the satellites, the constellation design, and the location of the parameter server. A comprehensive overview of the current state-of-the-art in this field is provided and the unique challenges and opportunities of satellite FL are discussed. Finally, we outline several open research directions for FL in satellite constellations and present some future perspectives on this topic.

Opportunities and challenges of on-board AI-based image recognition for small satellite Earth observation missions

The satellite industry is rapidly growing. There has been a significant increase in the number of new small satellites that are launched, which is complemented by the rapid pace of the development of image recognition algorithms. Convolutional neural networks (CNNs) in particular, have achieved state-of-the-art performance in computer vision related applications. Combining both and running an AI algorithm on-board the satellite to observe and recognize any natural disaster directly from the orbit is an important opportunity. This paper presents notable challenges that are generally involved in an Earth Observation small satellite mission and further challenges that are posed by combining it with AI-based image recognition on-board the satellite. This study discusses an approach that is feasible mainly for a fleet of small satellites.

Synergistic polyimide&ZrO2 flexible films enable low solar absorption and excellent wave-transparency

Carbon fiber epoxy resin (CFRP), as space satellite antenna materials with great application prospects to transmit and receive signals. It is necessary to ensure its normal operation through surface thermal control, which can be achieved by covering with a flexible film. Polyimide (PI) films modified by ceramics particle have been widely studied in the field of flexible devices. However, there is no research on multifunctional PI films with thermal control and wave transmission multifunctional performance. In this study, ZrO2 modified flexible PI films (PI/ZrO2 films) which can be covered on the surface of satellite antenna was prepared, and its solar absorption and wave transmission properties were studied. Prepared films exhibited excellent heat resistance and mechanical properties, and the addition of ZrO2 increased their thermal stability. The solar absorption of films with 50% ZrO2 is the lowest for 0.30, and the highest reflectance can reach to 88.4%. In addition, the maximum dielectric constant of the films was less than 2.5, and the dielectric loss was less than 0.03, showing an excellent wave transmission performance. The films can be covered on the satellite antenna, and also can be used for other space environment or wave transmission requirements.

Results and Perspectives of Timepix Detectors in Space—From Radiation Monitoring in Low Earth Orbit to Astroparticle Physics

In space application, hybrid pixel detectors of the Timepix family have been considered mainly for the measurement of radiation levels and dosimetry in low earth orbits. Using the example of the Space Application of Timepix Radiation Monitor (SATRAM), we demonstrate the unique capabilities of Timepix-based miniaturized radiation detectors for particle separation. We present the incident proton energy spectrum in the geographic location of SAA obtained by using Bayesian unfolding of the stopping power spectrum measured with a single-layer Timepix. We assess the measurement stability and the resiliency of the detector to the space environment, thereby demonstrating that even though degradation is observed, data quality has not been affected significantly over more than 10 years. Based on the SATRAM heritage and the capabilities of the latest-generation Timepix series chips, we discuss their applicability for use in a compact magnetic spectrometer for a deep space mission or in the Jupiter radiation belts, as well as their capability for use as single-layer X- and γ-ray polarimeters. The latter was supported by the measurement of the polarization of scattered radiation in a laboratory experiment, where a modulation of 80% was found.

Gradient calculation techniques for multi-point ionosphere/thermosphere measurements from GDC

The upcoming Geospace Dynamics Constellation (GDC) mission aims to investigate dynamic processes active in Earth’s upper atmosphere and their local, regional, and global characteristics. Achieving this goal will involve resolving and distinguishing spatial and temporal variability of ionospheric and thermospheric (IT) structures in a quantitative manner. This, in turn, calls for the development of sophisticated algorithms that are optimal in combining information from multiple in-situ platforms. This manuscript introduces an implementation of the least-squares gradient calculation approach previously developed by J. De Keyser with the focus of its application to the GDC mission. This approach robustly calculates spatial and temporal gradients of IT parameters from in-situ measurements from multiple spacecraft that form a flexible constellation. The previous work by De Keyser, originally developed for analysis of Cluster data, focused on 3-D Cartesian geometry, while the current work extends the approach to spherical geometry suitable for missions in Low Earth Orbit (LEO). The algorithm automatically provides error bars for the estimated gradients as well as the scales over which the gradients are expected to be constant. We evaluate the performance of the software on outputs of high-resolution global ionospheric/thermospheric simulations. It is shown that the software will be a powerful tool to explore GDC’s ability to answer science questions that require gradient calculations. The code can also be employed in support of Observing System Simulation Experiments to evaluate suitability of various constellation geometries and assess the impact of measurement sensitivities on addressing GDC’s science objectives.

Application of Three-Dimensional CFD Model to Determination of the Capacity of Existing Tyrolean Intake

CFD models of intakes in high-head hydropower systems are rare due to the lack of geometric data and cost of modeling. This study tests two different types of software to see how modeling can be performed in a cost-effective way with scarce input data and still have sufficient accuracy. The volume of fluid (VoF) model simulations are conducted using both ANSYS Fluent and OpenFOAM. The geometry is modelled from Google Earth satellite images, drone scanning data, and design drawings from the construction period and supported by field observations for extra quality control. From the model, both capacity parameters and flow pattern are calculated. For capacity, the Cd factor is calculated and compared with the literature. The simulations are conducted for a Tyrolean weir with rectangular bars (flat steel) in the rack. Simulated flow patterns through the rack with ANSYS Fluent and OpenFOAM are compared. OpenFOAM simulations yielded 15% to 20% higher water levels compared to the VOF model applied in Ansys Fluent. Also, when the flow rate was high, the water capture capacity calculated with ANSYS Fluent was 10% higher than that obtained with OpenFOAM. However, considering the total simulation times, modeling with OpenFOAM offered approximately 11% faster results.