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This paper presents an empirical study of dynamic factors affecting link quality in Low Earth Orbit (LEO) satellite communications, using Starlink as a case study. Over 56 days, 112 high-quality meteorological measurements in mostly 1-min intervals, co-located with a user terminal, were collected, alongside frequent network performance data. Cloud characteristics were estimated using professional weather instruments such as a ceilometer, microwave radiometer, and vision-language model on sky images. Our results show that general cloud presence does not significantly impact throughput or latency. The impact of cloud coverage rather depends on the presence of liquid water in the atmosphere, quantified by liquid water path (LWP), which correlates with notable download throughput reductions (up to 60 MBit/s), especially during rain. Upload and latency were largely unaffected. Analysis of the evolving satellite network revealed that newer satellite hardware and infrastructural upgrades also contributed to performance increases during the experiment period. These findings highlight atmospheric liquid water as the key weather-related factor affecting link quality and underscore the influe

Any knot in a solid torus, called a pattern or satellite operator, acts on knots in the 3-sphere via the satellite construction. We introduce a generalization of satellite operators which form a group (unlike traditional satellite operators), modulo a generalization of concordance. This group has an action on the set of knots in homology spheres, using which we recover the recent result of Cochran and the authors that satellite operators with strong winding number $\pm 1$ give injective functions on topological concordance classes of knots, as well as smooth concordance classes of knots modulo the smooth 4--dimensional Poincare Conjecture. The notion of generalized satellite operators yields a characterization of surjective satellite operators, as well as a sufficient condition for a satellite operator to have an inverse. As a consequence, we are able to construct infinitely many non-trivial satellite operators P such that there is a satellite operator $\overline{P}$ for which $\overline{P}(P(K))$ is concordant to K (topologically as well as smoothly in a potentially exotic $S^3\times [0,1]$) for all knots K; we show that these satellite operators are distinct from all connected-su

The growing number of satellite constellations in low Earth orbit (LEO) enhances global communications and Earth observation, and support of space commerce is a high priority of many governments. At the same time, the proliferation of satellites in LEO has negative effects on astronomical observations and research, and the preservation of the dark and quiet sky. These satellite constellations reflect sunlight onto optical telescopes, and their radio emission impacts radio observatories, jeopardising our access to essential scientific discoveries through astronomy. The changing visual appearance of the sky also impacts our cultural heritage and environment. Both ground-based observatories and space-based telescopes in LEO are affected, and there are no places on Earth that can escape the effects of satellite constellations given their global nature. The minimally disturbed dark and radio-quiet sky is crucial for conducting fundamental research in astronomy and important public services such as planetary defence, technology development, and high-precision geolocation. Some aspects of satellite deployment and operation are regulated by States and intergovernmental organisations. While

Solar Cycle 25 has run far stronger than the 2019 consensus forecast issued by the NOAA/NASA/ISES prediction panel, with densities in low Earth orbit from 2022-2026 holding at 2-3x the predicted levels. The cumulative drag impulse experienced by LEO satellites reached 5-6 standard deviations beyond the forecast's stated uncertainty. This means that even operators who designed conservatively against the two-sigma worst case fell short of their drag budgets. This paper quantifies a lower bound on the economic cost of that misprediction. Starting from the 13,704 payloads on-orbit below 800 km during 2022-2026, we screen to the 1,597 payloads which we validated with high confidence to be both operational and in ballistic freefall. We estimate each satellite's ballistic coefficient and propagate its trajectory under the forecasted atmosphere versus the observed one. A probabilistic cost model assigns each satellite an annualized mission cost based on direct costs (amortized capital costs plus annual operations), stratified by size class, with bespoke estimates for high value missions. Survival and forward cost discounting is applied at a modal 11% per year. We combine the differences in

To address the need for robust positioning, navigation, and timing services in lunar environments, this paper proposes a novel fault detection framework for satellite constellations using inter-satellite ranging (ISR). Traditionally, navigation satellites can depend on a robust network of ground-based stations for fault monitoring. However, due to cost constraints, a comprehensive ground segment on the lunar surface is impractical for lunar constellations. Our approach leverages vertex redundantly rigid graphs to detect faults without relying on precise ephemeris. We model satellite constellations as graphs where satellites are vertices and inter-satellite links are edges. We identify faults through the singular values of the geometric-centered Euclidean distance matrix (GCEDM) of 2-vertex redundantly rigid sub-graphs. The proposed method is validated through simulations of constellations around the Moon, demonstrating its effectiveness in various configurations. This research contributes to the reliable operation of satellite constellations for future lunar exploration missions.

The galaxy system around NGC4490 was recently highlighted to display a flattened, kinematically correlated structure reminiscent of satellite galaxy planes around other hosts. Since known satellite planes are in tension with $Λ$CDM expectations from cosmological simulations, we quantitatively assess for the first time the tension posed by the NGC4490 system. We measure the on-sky flattening as the major-to-minor axis ratio b/a of the satellite distribution and their line-of-sight kinematic correlation. Analogs are selected in the IllustrisTNG-50 simulation and their flattening and correlation are similarly measured. We confirm the strong kinematic coherence of all 12 observed objects with available line-of-sight velocities (of 14 in total): the northern ones approach and the southern ones recede relative to the host. The spatial distribution of all 14 objects is substantially flattened with b/a=0.38 (0.26 considering only the 12 objects with velocities). Such extreme arrangements are rare in the simulation at 0.21-0.35%. This would drop further if at least one of the two satellite objects without velocities is confirmed to follow the kinematic trend, and would become zero if both a

Modern Earth Observation (EO) missions generate massive volumes of imagery that challenge existing downlink and ground-processing capabilities, particularly for time-critical applications. This work investigates how a low Earth orbit (LEO) satellite constellation equipped with heterogeneous edge computing resources can enable real-time semantic processing of data acquired by EO satellites. We introduce an energy-aware framework that optimizes the use of resources accounting for data acquisition, computing, and communication constraints. Although we focus on maritime surveillance, the formulation is task-agnostic and accommodates a broad class of semantic and goal-oriented inference problems. Specifically, we formulate two coupled optimization problems: (i) observation scheduling, which selects image acquisition opportunities while accounting for turbulence-induced image degradation and energy budget, and (ii) processing scheduling, which allocates semantic workloads across onboard and ground processors. We evaluate these mechanisms for the task of detection and localization of vessels, for which we quantify the benefits of turbulence-aware observation scheduling for preserving imag

Direct-to-cell connectivity between satellites and common terrestrial handheld devices represents an essential feature of 6G. The industry is considering different type of constellations but using classical single satellite solutions based on phased array antennas. This article proposes to decompose a classical single satellite into a swarm of multiple small platforms (e.g. CubeSats) each equipped with one or a small number of radiating elements. The platforms are spaced far apart to create a large virtual aperture. The use of small satellites promises cost reduction for production and launch, while the distributed nature of the system introduces interesting features, such as scalability and fault tolerance. This perspective article provides insights into the opportunities and a discussion of the research challenges for the feasibility of the proposed approach.

The mean apparent magnitude of the Qianfan satellites is 5.76 +/- 0.04, while the mean of magnitudes adjusted to a distance of 1,000 km is 5.24 +/- 0.04, based on 1,161 observations. Light curves of several spacecraft display rapid periodic fluctuations which indicate that they are tumbling. Nearly all of the non-tumbling satellite observations can be modeled with diffusely reflecting, Earth-facing surfaces. The Qianfan constellation will impact astronomical research and aesthetic appreciation of the night sky unless their brightness is mitigated.

Novel deep-learning (DL) architectures have reached a level where they can generate digital media, including photorealistic images, that are difficult to distinguish from real data. These technologies have already been used to generate training data for Machine Learning (ML) models, and large text-to-image models like DALL-E 2, Imagen, and Stable Diffusion are achieving remarkable results in realistic high-resolution image generation. Given these developments, issues of data authentication in monitoring and verification deserve a careful and systematic analysis: How realistic are synthetic images? How easily can they be generated? How useful are they for ML researchers, and what is their potential for Open Science? In this work, we use novel DL models to explore how synthetic satellite images can be created using conditioning mechanisms. We investigate the challenges of synthetic satellite image generation and evaluate the results based on authenticity and state-of-the-art metrics. Furthermore, we investigate how synthetic data can alleviate the lack of data in the context of ML methods for remote-sensing. Finally we discuss implications of synthetic satellite imagery in the contex

Small satellites are integral to scientific, commercial, and defense missions, but reliance on commercial off-the-shelf (COTS) hardware broadens their attack surface. Although supply chain threats are well studied in other cyber-physical domains, their feasibility and stealth in space systems remain largely unexplored. Prior work has focused on flight software, which benefits from strict security practices and oversight. In contrast, auxiliary COTS components often lack robust assurance yet enjoy comparable access to critical on-board resources, including telemetry, system calls, and the software bus. Despite this privileged access, the insider threat within COTS hardware supply chains has received little attention. In this work, we present SpyChain, the first end-to-end design and implementation of independent and colluding hardware supply chain threats targeting small satellites. Using NASA's satellite simulation (NOS3), we demonstrate that SpyChain can evade testing, exfiltrate telemetry, disrupt operations, and launch Denial of Service (DoS) attacks through covert channels that bypass ground monitoring. Our study traces an escalation from a simple solo component to dynamic, coo

In this paper, we develop a high-precision satellite orbit determination model for satellites orbiting the Earth. Solving this model entails numerically integrating the differential equation of motion governing a two-body system, employing Fehlberg's formulation and the Runge-Kutta class of embedded integrators with adaptive stepsize control. Relevant primary perturbing forces included in this mathematical model are the full force gravitational field model, Earth's atmospheric drag, third body gravitational effects and solar radiation pressure. Development of the high-precision model required accounting for the perturbing influences of Earth radiation pressure, Earth tides and relativistic effects. The model is then implemented to obtain a high-fidelity Earth orbiting satellite propagator, namely the Satellite Ephemeris Determiner (SED), which is comparable to the popular High Precision Orbit Propagator (HPOP). The architecture of SED, the methodology employed, and the numerical results obtained are presented.

Low latency and high synchronization among users are critical for emerging multi-user virtual interaction applications. However, the existing ground-based cloud solutions are naturally limited by the complex ground topology and fiber speeds, making it difficult to pace with the requirement of multi-user virtual interaction. The growth of low earth orbit (LEO) satellite constellations becomes a promising alternative to ground solutions. To fully exploit the potential of the LEO satellite, in this paper, we study the satellite server selection problem for global-scale multi-user interaction applications over LEO constellations. We propose an effective server selection framework, called SpaceMeta, that jointly selects the ingress satellite servers and relay servers on the communication path to minimize latency and latency discrepancy among users. Extensive experiments using real-world Starlink topology demonstrate that SpaceMeta reduces the latency by 6.72% and the interquartile range (IQR) of user latency by 39.50% compared with state-of-the-art methods.

Satellite constellation interference occurs across astronomical disciplines. We present examples of interference from radio and $γ$-Ray astronomy to optical and spectroscopic interference in ground-based and space-borne facilities. In particular, we discuss the impact of artificial satellites on the Hubble Space Telescope (HST), the High Energy Stereoscopic System (H.E.S.S.), an Imaging Atmospheric Cherenkov Telescope, as well as possible mitigation strategies for the European Southern Observatory 4-metre Multi-Object Spectrograph Telescope (ESO 4MOST). Furthermore, we shed light on how ground-based optical telescopes such as the Oukaimeden Observatory contribute to IAU Centre for the Protection of the Dark and Quiet Sky from Satellite Constellation Interference (IAU CPS) efforts that quantify satellite brightness.

In Non-Terrestrial Networks (NTN), achieving effective radio resource allocation across multi-satellite system, encompassing efficient channel and bandwidth allocation, effective beam management, power control and interference mitigation, poses significant challenges due to the varying satellite links and highly dynamic nature of user traffic. This calls for the development of an intelligent decision-making controller using Artificial Intelligence (AI) to efficiently manage resources in this complex environment. In this context, open datasets can play a crucial role in driving new advancement and facilitating research. Recognizing the significance, this paper aims to contribute the satellite communication research community by providing various open datasets that incorporate realistic traffic flow enabling a variety of uses cases. The primary objective of sharing these datasets is to facilitate the development and benchmarking of advanced resource management solutions, thereby improving the overall satellite communication systems. Furthermore, an application example focused on beam placement optimization via terminal clustering is provided. This assists in optimizing beam allocatio

SatHub is one of the four hubs of the IAU Centre for the Protection of the Dark and Quiet Sky from Satellite Constellation Interference (CPS). It focuses on observations, data analysis, software, and training materials to improve our understanding of the impact of satellite constellations on astronomy and observers worldwide. As a preface to more in-depth IAUS385 sessions, we gave a summary of some recent work by SatHub members and the current status of satellite constellations, including optical and radio observations. We shared how the audience can join or get more involved, e.g., via the CPS Slack for asynchronous collaboration. We also touched on what a future with hundreds of thousands of constellation satellites might look like.

Satellite clock bias prediction plays a crucial role in enhancing the accuracy of satellite navigation systems. In this paper, we propose an approach utilizing Long Short-Term Memory (LSTM) networks to predict satellite clock bias. We gather data from the PRN 8 satellite of the Galileo and preprocess it to obtain a single difference sequence, crucial for normalizing the data. Normalization allows resampling of the data, ensuring that the predictions are equidistant and complete. Our methodology involves training the LSTM model on varying lengths of datasets, ranging from 7 days to 31 days. We employ a training set consisting of two days' worth of data in each case. Our LSTM model exhibits exceptional accuracy, with a Root Mean Square Error (RMSE) of 2.11 $\times$ 10$^{-11}$. Notably, our approach outperforms traditional methods used for similar time-series forecasting projects, being 170 times more accurate than RNN, 2.3 $\times$ 10$^7$ times more accurate than MLP, and 1.9 $\times$ 10$^4$ times more accurate than ARIMA. This study holds significant potential in enhancing the accuracy and efficiency of low-power receivers used in various devices, particularly those requiring power

In the current study, we explore stability of motion of satellite around the natural moons of planets in Solar system using the novel concept of ER3BP with variable eccentricity. This concept was introduced earlier when novel type of ER3BP (Sun-planet-satellite) was investigated with variable spin state of secondary planet correlated implicitly to the motion of satellite (in the synodic co-rotating Cartesian coordinate system) for its trapped orbit near the secondary planet (which is involved in kepler duet <Sun-planet>). But it is of real interest to explore another kind of aforedescribed problem, ER3BP (planet-moon-satellite) with respect to investigation of motion of satellite m around the natural moon m_moon of planet in Solar system with variable eccentricity of the moon in its motion around the planet. So, we consider here two primaries, M_planet and m_moon, the last is orbiting around their common barycenter on quasi-elliptic orbit with slow-changing, not constant eccentricity (on a large-time scale) due to tidal phenomena. Our aim is to investigate motion of small dot satellite around the natural moon of planet on quasi-stable elliptic orbit. Both novel theoretical an

A novel approach for solving equations of motion of finite-sized satellite supposed to be moving in a proximity and around the planet in the elliptic restricted three-body problem, ER3BP is presented in this semi-analytical investigation. We consider two primaries, M_Sun and m_planet (the last is secondary in that binary system), both are orbiting around their barycenter on elliptic orbits. Satellite is considered to be the solid ellipsoid having nearly spherical form, with its gravitational potential to be given by a formula of MacCullagh type. Our aim is to revisit previously presented in work [Ashenberg, 1996] approach and to investigate the updated type of the satellite dynamics correlated implicitly to a kind of trapped motion (in the synodic co-rotating Cartesian coordinate system) in so way that satellite will always to be located near the secondary planet, m_planet, moving on quasi-stable elliptic orbit.