Search Results (373)

Direct-to-cell (D2C) non-terrestrial networks (NTNs) based on 5G technology are emerging as a key complement to terrestrial cellular networks, extending connectivity to underserved and remote areas while enabling integration with existing mobile ecosystems. As these systems begin operating in frequency bands already used by terrestrial International Mobile Telecommunications (IMT) networks, coexistence becomes critical. This paper presents a victim-centric methodology for evaluating D2C interference into terrestrial 5G networks in the 694/698 MHz-2.7 GHz regulatory study range. Seven downlink carrier cases and four uplink carrier cases between 734 and 2620 MHz are evaluated. For a prescribed external interference-to-noise ratio, the external contribution is referenced to receiver thermal noise, while terrestrial intra-network interference remains part of the baseline and interfered signal-to-interference-plus-noise ratio (SINR). The resulting throughput loss is translated into candidate power-flux-density (PFD) and equivalent-power-flux-density (EPFD) protection levels. A reference non-geostationary-satellite-orbit (NGSO) system is used only to motivate the assumed receiver-exposure fractions; the numerical network results are therefore conditional on those exposure assumptions. The same external interference level produces approximately three times greater network throughput loss at base stations than at user equipment, so direction-specific protection levels are required. For downlink protection, the tested 3 dB noise-rise case gives candidate PFD levels from −109.23 to −98.17 dB(W/(m²·MHz)); for opposite-direction cross-border uplink protection, I/N = −6 dB gives candidate EPFD levels from −138.23 to −130.18 dB(W/(m²·MHz)) for non-AAS base stations. The approximately 11 dB offset for AAS cases results from the maximum-gain normalization used in EPFD and should not be interpreted as evidence of greater satellite exposure. These values are tested candidate levels rather than estimates of an exact 5% crossing point. Full article

Spacecraft radiation assessment requires expert interpretation of continuous environment-model outputs. We present a reflection-equivariant Mamdani fuzzy system for relative triage of modelled total ionising dose (TID) and solar-proton exposure. Radiation environment severity and solar-proton severity are derived from OMERE 5.9.5 runs of the AE9/AP9 (IRENE 1.57.004, mean mode) and Emission of Solar Protons (ESP, 90 per cent confidence) models, and, together with mission duration, are mapped through reflection-paired membership partitions and a 27-rule sum-based rule base to four triage categories. We prove reflection symmetry of the input and output partitions, permutation symmetry of the rule map, risk-reversal duality of the aggregated inference and centroid score, and reflection equivariance of a normalised output-support vector retained before defuzzification. The architecture is examined on nine reference mission scenarios and additional boundary cases using sensitivity, comparative-variant and cumulative-versus-duration-normalised analyses. The results show exact algebraic consistency with the imposed symmetry identities and transparent rule-level traceability, while also revealing the small local non-monotonicity of the centroid score and formulation sensitivity in the seven-year GLONASS-like scenario. Under the integrated-exposure formulation, scores range from 0.381 for the polar low-Earth-orbit scenario to 0.892 for the geostationary orbit (GEO). Because the same nine scenarios also define the frozen normalisation anchors, this range is a reference-set demonstration rather than an out-of-sample result. Evaluation to date comprises internal mathematical-consistency checks, comparison with an author-defined conservative heuristic and concordance with a seven-member expert panel blinded to the model output but rating the same scenario descriptions; the system has not been validated against ground-truth radiation-hardness outcomes such as mission anomaly records or component-qualification results. Cases for which the integrated and duration-normalised diagnostics disagree are flagged for separate engineering analysis. The system is a reference-benchmarked proof-of-concept pre-screening method and does not replace project-specific TID, total non-ionising dose (TNID), single-event-effect, shielding or component-qualification analysis. Full article

Formic acid (HCOOH), the most abundant carboxylic acid in the troposphere, modulates rainwater acidity, aerosol water uptake, and the oxidative capacity of remote atmospheres, yet its global budget remains poorly constrained. Herein, we present the first HCOOH total-column retrieval from thermal–infrared (TIR) measurements of the Thermal And Near-infrared Sensor for carbon Observation Fourier Transform Spectrometer-2 (TANSO-FTS-2) on board GOSAT-2, providing an early-afternoon observational perspective that complements existing morning low-Earth-orbit and geostationary HCOOH products. The Optimal Estimation retrieval sequentially fits the surface state, the atmospheric background (temperature, water vapor and ozone), and the HCOOH profile in a 1104–1109 cm⁻¹ microwindow centered on the ${\nu }_6$ Q-branch, with a radiance-ratio-scaled a priori that adapts to each scene. Averaging-kernel diagnostics concentrate the sensitivity in the 500–900 hPa layer with degrees of freedom for signal of approximately 1.05 under enhanced-emission conditions. For a 2019–2020 Australian bushfire case, including HCOOH in the state vector reduces the mean spectral residual from −0.327 K to 0.033 K. Independent evaluation against 113 time-coincident Toronto NDACC FTIR overpasses gives R = 0.95 and a zero-intercept slope of 2.12 for raw FTIR versus GOSAT-2. Applying the GOSAT-2 a priori and averaging kernel to the FTIR profiles changes the slope to 0.77 and reduces the RMSE to $0.23\times {10}^{16}$ molec cm⁻²; this one-sided smoothing is treated only as a sensitivity diagnostic. Monthly global maps for December 2019 and June 2020 show cross-sensor consistency with the IASI/MetOp-B ANNI-HCOOH product at R = 0.83 and 0.76. Over East Asia during April–June 2023, GOSAT-2 correlates with FY-4B/GIIRS at R = 0.90 (April) and R = 0.65 (June), with coherent three-sensor daily variability. These satellite comparisons are treated as cross-sensor consistency assessments rather than independent validation. GOSAT-2 consistently reports lower columns, a sensitivity-limited tendency consistent with a priori dominance under weak signals, limited information content, a narrow retrieval window, and differences among retrieval frameworks. The current product is a first demonstration for cloud-free daytime land scenes; this domain defines its sampling scope and representativeness but is not interpreted as a direct cause of the lower columns. The product offers a traceable GOSAT-2 TIR observational constraint on tropospheric HCOOH for future multi-platform synergy. Full article

High-precision frequency standards underpinning signal synchronization and data consistency are essential for satellites. Navigation satellites use atomic clocks as time and frequency standards; however, limitations in size, weight, and cost constrain their performance. Geostationary Earth orbit (GEO) communication satellites typically rely on onboard oscillators as references, whose performance is generally poor. Moreover, satellite–ground links can be used for frequency synchronization between GEO satellites and ground stations. However, phase drift in onboard oscillators restricts improvements in synchronization precision. This paper introduces a frequency synchronization method based on a beacon transponder that enables ground stations to calculate and eliminate satellite oscillator phase drift. This design achieves high-precision frequency synchronization through real-time carrier-phase compensation and replicates the ground station’s frequency standard onboard. Ground-based experiments validated the method using a beacon transponder prototype in motion. The standard deviation of the phase synchronization error between the replicated clock and ground-station frequency standard was 2.97 ps over 24 h. The stability was better than 2.61 × 10⁻¹² and 9.98 × 10⁻¹⁶ for averaging times of 1 s and 10,000 s, respectively. These results demonstrate this method’s potential for high-precision frequency synchronization between satellites and ground stations, crucial for establishing an integrated space–air–ground frequency synchronization network. Full article

The geostationary hyperspectral infrared sounder (GeoHIS) provides atmospheric variables at high spatiotemporal resolution. Consequently, GeoHIS can provide valuable information for improving real-time forecasting and enhancing the performance of numerical weather prediction (NWP). GeoHIS provides higher temporal resolution than that of a polar-orbiting platform, observing the same region 2~3 times daily. Therefore, we assess the forecast impact of a next-generation GeoHIS on a numerical model according to observation density using KIM-OSSE (Korean Integrated Model–Observing System Simulation Experiment) in this study. Simulated observations are generated from the nature run dataset (ECO 1280) provided by Cooperative Institute for Research in the Atmosphere at Colorado State University (CIRA/CSU). These simulated observations are then assimilated into KIM, after which KIM generates forecast fields. Using this framework, we evaluated the impact of GeoHIS on a global numerical model. The results showed noticeable improvements in geopotential height, particularly in the mid- and upper troposphere, while wind, temperature, and humidity remain largely unchanged in EXP-1 and EXP-2. An analysis of the sensitivity to GeoHIS temporal resolution, by comparing hourly data and 3-hourly data, revealed that higher temporal resolution leads to greater forecast improvements. Full article

Although prehistoric rock art shelters in remote locations require continuous environmental monitoring for preventive conservation, this need is frequently hindered by the absence of terrestrial connectivity. In this study, we present and validate a hybrid Internet of Things (IoT) monitoring architecture integrating low-power Long-Range Wide-Area Network (LoRaWAN) wireless ground-based sensors, edge computing, and dual terrestrial–satellite connectivity, designed for continuous climatic monitoring in heritage areas without terrestrial connectivity coverage. This proof of concept was conducted at the rock art shelter of Los Toros del Barranco de las Olivanas (Tormón, Teruel, Spain), a United Nations Educational, Scientific and Cultural Organization (UNESCO) World Heritage Site within the Albarracín Cultural Park (PCA), using Geostationary Earth Orbit (GEO) satellite connectivity provided by EchoStar Mobile. Laboratory and outdoor tests at the Universitat Politècnica de València (UPV) achieved a satellite data delivery rate of 98.6%, while field deployment under adverse conditions—partial vegetation and terrain obstructions, cloudy and rainy weather—yielded a delivery rate of 78.2%, with 100% delivery from sensors to the edge gateway. The system operates below 10 W, enabling autonomous solar-powered deployment. Reliability can be raised above 95% by having the system confirm that each message is received and by managing the order in which messages are sent. The architecture reduces on-site visits by an estimated 75%, significantly lowering the carbon footprint of field campaigns. The proposed system is flexible, scalable, and compatible with future Non-Terrestrial Networks (NTNs), demonstrating that a satellite IoT constitutes a technically feasible solution for continuous environmental monitoring of remote heritage sites worldwide. Full article

The BeiDou-3 Navigation Satellite System (BDS-3) broadcasts multi-frequency signals, including B1C, B2a, B1I, and B3I, offering a new technical approach for tilt monitoring of building structural safety. However, in building structural safety tilt monitoring based on the BDS-3 single-epoch algorithm, the engineering performance differences between the B1C/B2a new signal combination and the B1I/B3I traditional signal combination—in terms of monitoring accuracy, ambiguity fixing rate, computational efficiency, and tilt rate—have yet to be fully validated through comparative analysis. To address this issue, this paper proposes a building structural safety tilt monitoring method based on the BDS-3 single-epoch algorithm and conducts a field test on a multi-story building in Beijing. First, a BDS-3-based kinematic monitoring model is established, and an integer ambiguity error search band method based on the main and auxiliary frequencies is proposed. On this basis, three schemes are designed using medium Earth orbit (MEO), inclined geosynchronous orbit (IGSO), and geostationary Earth orbit (GEO) satellites, B1C/B2a (MEO/IGSO), B1I/B3I (MEO/IGSO), and B1I/B3I (MEO/IGSO/GEO), to comparatively analyze the accuracy, ambiguity fixing rate, computational efficiency, and measured tilt results of each scheme in building structural safety tilt monitoring. Experimental results show that all three schemes based on the BDS-3 single-epoch algorithm achieve millimeter-level monitoring accuracy and an ambiguity fixing rate exceeding 99%, with average computational times of 0.351 s, 0.338 s, and 4.572 s and corresponding building tilt rates of 0.22‰, 0.20‰, and 0.18‰, respectively, yielding an average tilt rate of 0.20‰. These results satisfy the 4‰ limit specified in the Code for Deformation Measurement of Building and Structure (JGJ 8-2016), thereby confirming the feasibility and effectiveness of the proposed method and offering a novel BDS-3 single-epoch algorithm for building tilt monitoring. Full article

Polar-orbiting microwave radiometers provide indispensable all-weather measurements of the atmospheric state, yet revisit intervals of many hours leave critical gaps during rapidly evolving weather events. To address this limitation, we developed MIDAS (Microwave Inference via Diffusion Across Satellites), a probabilistic framework that estimates microwave brightness temperature (BT) fields across the geostationary full-disk domain from infrared observations at 10 min intervals. This study focuses on the five Microwave Humidity Sounder-2 (MWHS-2) humidity-sounding channels near 183 GHz, which provide vertically resolved water vapor information. MIDAS achieves relative errors below 0.5% for the majority of cases, with a channel-averaged mean absolute error of 1.15 K, outperforming a deterministic U-Net baseline (1.43 K). Beyond per-sample evaluation, MIDAS reproduces large-scale climatological patterns across the full-disk domain over a three-month summer period, consistent with Radiative Transfer for TOVS–Scattering (RTTOV-SCATT) simulations. In deep convective scenes where reconstruction is most difficult, the ensemble spread naturally tracks reconstruction difficulty, providing a built-in indicator of prediction confidence. Notably, MIDAS incorporates real-time polar-orbiting observations as physical constraints via a merge-sampling mechanism, reducing ensemble RMSE by over 20% and improving probabilistic calibration by more than 30%. Proof-of-concept assimilation experiments for two high-impact weather cases show that MIDAS-generated fields yield forecast improvements comparable to those from real satellite observations, reducing tropical cyclone track errors from approximately 110 km to 40 km and improving heavy precipitation forecasts at extreme rainfall thresholds where direct infrared assimilation shows no benefit. Overall, our framework demonstrates the potential of generative models to supplement sparse observational coverage and provide physically plausible microwave humidity fields for downstream applications. Full article

With the rapid development of commercial aerospace, emerging applications such as satellite constellations, space-based communications, and orbital computing platforms have significantly increased the demand for efficient and reliable spacecraft power systems. Abundant exploitable energy exists in the space environment, including Air Mass Zero (AM0) solar radiation, spacecraft surface temperature gradients, ambient electromagnetic radiation, and radioisotope thermal energy, making multi-source energy harvesting a promising approach for improving satellite energy autonomy and system redundancy. This paper reviews the following four key space energy harvesting technologies: photovoltaic power generation, radio frequency (RF) energy harvesting, thermoelectric energy harvesting, and radioisotope thermoelectric generators (RTGs). The impacts of harsh space environmental factors on device performance and reliability are analyzed, and the applicability of different technologies in low Earth orbit (LEO), geostationary orbit (GEO), and deep-space missions is discussed. Furthermore, a multi-source self-powered satellite energy architecture integrating energy harvesting, energy storage, and power management is proposed. Finally, the major challenges and future development trends of satellite energy harvesting systems are summarized. Full article

Recurring spacecraft anomalies may reflect anomaly-prone system states shaped jointly by spacecraft geometry, recent anomaly history, and space weather forcing, rather than isolated responses to single external drivers. Distinguishing these contributions is important for interpretable anomaly monitoring in geostationary orbit. This study develops a satellite-stratified case–control framework for GOES-16/17 Extreme Ultraviolet and X-ray Irradiance Sensors (EXIS) Space Wire (SpW) anomaly records. Orbital–illumination descriptors, same-satellite event history variables, and space weather variables from the NASA OMNI database are integrated within chronological train–test validation, supported by null-baseline comparison, stratified bootstrap confidence intervals, exclusion window sensitivity analysis, feature group ablation, cross-satellite testing, and calibration diagnostics. Orbital–illumination variables provide weak but reproducible discrimination, event history descriptors capture temporal clustering, and space weather variables add complementary held-out information. The full Space Environment-Integrated Model (SEIM) reached a test area under the receiver operating characteristic curve (AUC) of 0.7540, while a compact train-only L1-selected clean Top-15 model achieved comparable held-out discrimination with a test AUC of 0.7588 after excluding direct near-neighbor history variables. Bootstrap comparisons indicate that this small difference is not statistically significant. Calibration diagnostics further confirm that fitted scores should be interpreted as discriminative anomaly-state indicators under the case–control design rather than as calibrated operational anomaly probabilities. Full article

Accurate short-term estimation of clear-sky Global Horizontal Irradiance (GHI) is vital for solar resource assessment and grid operations, yet existing methods rely on sparse radiometers and coarse global weather reanalysis (e.g., MERRA-2 at 50–70 km spatial resolution with 1 month latency). To achieve scalability in high-precision estimation, we propose a framework that removes dependence on ground measurements by combining multi-satellite observations with reanalysis variables in a physics-supervised machine-learning paradigm. We developed a multi-source-fused high-resolution environmental dataset with 5 min granularity and 1 km spatial precision, incorporating Geostationary Operational Environmental Satellite (GOES-16) observations, polar-orbiting satellite (AURA) data, and MERRA-2 reanalysis. As supervisory physics, we harmonized two complementary parameterized radiative transfer models (MAC2 and REST2V5). The harmonized GHI estimates are used as training labels for a Multilayer Perceptron (MLP) and a Residual Long Short-Term Memory (LSTM) network model. The trained MLP model achieved a root mean square error (RMSE) of 66.67 $\mathrm{W}/{\mathrm{m}}^2$, representing a 7.50% reduction over the conventional MERRA-2-driven baseline. For 30-min-ahead forecasting, the LSTM model reduced RMSE by 29.37% over the persistence baseline. Evaluated at four climatically diverse U.S. sites, the system achieves ground-sensor-like accuracy and is deployable anywhere within GOES-16 coverage. Full article

As 6G mobile communications evolve, Low Earth Orbit (LEO) satellite mobile edge computing (MEC) enables globally seamless computing. However, the high mobility of LEO satellites disrupts service continuity and resource stability. Existing approaches often use oversimplified models that ignore multi-beam interference and dynamic task queueing. To address this, we establish a hierarchical Geostationary Earth Orbit (GEO)–LEO synergistic architecture, where the integration is implemented by utilizing GEO satellites as stability anchors and remote cloud relays, while LEO satellites provide low-latency edge processing. We formulate fine-grained models for two-level beam-centric communication and preemptive dynamic queueing. The resulting joint task offloading and resource allocation problem is a complex mixed-integer nonlinear program (MINLP). To effectively solve this MINLP, we decouple it hierarchically: first determine discrete offloading decisions, then optimize continuous resource allocations based on them, proposing a novel framework termed G²DRL (GNN-enhanced Game-theoretic and deep reinforcement learning). Simulation results demonstrate that G²DRL significantly reduces the weighted sum of system delay and energy, showing superior convergence stability and performance over state-of-the-art DRL baselines. Full article

The launch of the Flexible Combined Imager (FCI) sensor aboard the Meteosat Third Generation (MTG) satellite enables higher temporal and spatial resolution for geostationary environmental monitoring. This study explores the feasibility of near-real-time fire detection using MTG-FCI data. Two unsupervised approaches are evaluated on data covering the Italian territory: a conventional threshold method, applying fixed radiometric thresholds and brightness temperature differences between 3.8 μm and 10.5 μm, and an experimental Lightweight U-Net autoencoder for anomaly detection. The autoencoder is trained exclusively on fire-free imagery, with fires identified as statistical anomalies in the reconstruction error, refined through local and global z-score analysis. Validation combines high-resolution Sentinel-2 imagery, Fire Radiative Power (FRP) and data from European Forest Fire Information System (EFFIS). Results demonstrate that MTG-FCI can trigger active fire alerts prior to polar overpasses in $67.32\%$ of the synchronized cases, providing a median early detection lead time of 21.00 min and reaching an advance of up to approximately 6 h in exceptional instances. While the spatial resolution limits detailed fire-front mapping, the high temporal resolution enables a robust near-real-time alerting system, providing enhanced detection of transient fire events that are not captured by lower-frequency polar-orbiting sensors. Full article

To realise high-speed free-space optical communication links in harsh space environments, it is crucial to consider the link’s operating wavelength, the performance of the optical receiver, and the radiation hardness of the avalanche photodiode (APD)—optical detectors in the optical receivers. In this work, we experimentally evaluated the radiation hardness of 2.5 Gb/s receivers based on InGaAs/AlGaAsSb APDs integrated with Ommic CGY2102UH/C2 transimpedance amplifiers. Proton energy (62 MeV) and fluence (up to 3.8 × 10¹⁰ p/cm²) representative of space environments were used to irradiate multiple receivers, ensuring rigour. After irradiation, the receivers maintained their avalanche gain and photocurrent, while exhibiting bandwidths exceeding 1.5 GHz. Despite a slight increase in APD’s dark current at high reverse bias, there was no degradation of the receiver’s bit error rate. At 2.5 Gb/s data rate and 1550 nm wavelength, the irradiated receivers achieved a bit error rate of 10⁻⁹ with an average optical power of −38.2 dBm, outperforming selected commercial receivers by ~3 dB. Since the displacement damage dose induced by the proton radiation levels used in this work are representative of those in Low Earth, Geostationary and Global Positioning System orbits, we demonstrated that InGaAs/AlGaAsSb APDs have sufficient radiation hardness to be employed as optical detectors of high-speed optical links in harsh space environments. Full article

The high environmental toll of terrestrial data centers described by their high land and water footprint has motivated new data center solutions. An important solution that has emerged from this motive is the space-based data center (SBDC). An SBDC is a space asset capable of processing the increased amount of data arising from space-based applications. Being in a non-geostationary earth orbit, it is important for important high-capacity hyper-scale space-based data centers to be capable of transmitting data to ground stations where valuable applications are hosted. This challenge necessitates addressing the maximum use of communication windows for non-geostationary space assets requiring further research attention. The research presented proposes an algorithm enabling the scheduling of power for optimal communication window functioning, to achieve high quality of service and make the best use of a communication window opportunity. This is achieved by increasing the power available to the SBDC communication subsystem. The evaluation shows that using the proposed approach enhances communication window utilization readiness and the communication window by 82.8% and 55.9% on average, respectively. Full article