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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

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

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.

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.

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

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

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.

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

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

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.

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

Future satellite networks are expected to have thousands of low Earth orbit (LEO) satellites orbiting Earth at very high speeds. User equipment (UE) communicating directly with LEO satellites will experience frequent handovers. Managing the handover process is complicated due to the high frequency of handovers and the availability of multiple LEO satellites as handover targets. In addition, as the status of the communication link between a UE and an LEO satellite varies in accordance with the visibility period of the satellite, initiating handovers at the right time will significantly affect the quality of service (QoS) of the communication provided. To address this problem, this work proposes a graph-based customizable handover framework that considers both the handover timing and target while selecting a handover sequence that maintains QoS. A time-based graph is designed where the vertices represent the satellites' instances over a certain period of time and the edges' weights are the customizable handover criteria (i.e., data rate and delay in this work). The appropriate sequence and timing of handovers that fulfill the required QoS are obtained by finding the shortest path in

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

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

Quantifying the connection between galaxies and their host dark matter halos has been key for testing cosmological models on various scales. Below $M_\star \sim 10^9\,M_\odot$, such studies have primarily relied on the satellite galaxy population orbiting the Milky Way. Here we present new constraints on the connection between satellite galaxies and their host dark matter subhalos using the largest sample of satellite galaxies in the Local Volume ($D \lesssim 12\,\mathrm{Mpc}$) to date. We use $250$ confirmed and $71$ candidate dwarf satellites around 27 Milky Way (MW)-like hosts from the Exploration of Local VolumE Satellites (ELVES) Survey and use the semi-analytical SatGen model for predicting the population of dark matter subhalos expected in the same volume. Through a Bayesian model comparison of the observed and the forward-modeled satellite stellar mass functions (SSMF), we infer the satellite stellar-to-halo mass relation. We find that the observed SSMF is best reproduced when subhalos at the low mass end are populated by a relation of the form $M_\star \propto M^α_\mathrm{peak}$, with a moderate slope of $α_\mathrm{const}=2.10 \pm 0.01$ and a low scatter, constant as a fun

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.

With the development of the massive satellite constellation and the on-orbit laser-based communication equipment, the wavelength routing optical satellite network (WROSN) becomes a potential solution for on-orbit, high-capacity, and high-speed communication. Since the inter-satellite links (ISLs) are time-varying, one of the fundamental considerations in the construction of the WROSN is assigning limited laser communication terminals for each satellite to establish ISLs with the visible satellites. Therefore, we propose a links assignment scheme (LAS) based on the potential edges importance matrix (PEIM) algorithm to construct a temporarily stable topology of the ISLs for a dual-layer constellation. The simulation results showed that the LAS based on the PEIM algorithm is better than LAS based on the random or Greedy algorithm in terms of node-to-node distance, node pair connectivity, wavelength demand, and transmission delay. The node pair connectivity and wavelength demand in WROSN is a trade-off problem. The research in this paper also brings a novel method for reduction of the cost of the on-board resources, that is through designing topology of the ISLs with links assignment a

A RL (Reinforcement Learning) algorithm was developed for command automation onboard a 3U CubeSat. This effort focused on the implementation of macro control action RL, a technique in which an onboard agent is provided with compiled information based on live telemetry as its observation. The agent uses this information to produce high-level actions, such as adjusting attitude to solar pointing, which are then translated into control algorithms and executed through lower-level instructions. Once trust in the onboard agent is established, real-time environmental information can be leveraged for faster response times and reduced reliance on ground control. The approach not only focuses on developing an RL algorithm for a specific satellite but also sets a precedent for integrating trusted AI into onboard systems. This research builds on previous work in three areas: (1) RL algorithms for issuing high-level commands that are translated into low-level executable instructions; (2) the deployment of AI inference models interfaced with live operational systems, particularly onboard spacecraft; and (3) strategies for building trust in AI systems, especially for remote and autonomous applica