Low Earth Orbit Research Articles

This study investigates how sustained low Earth orbit (LEO) exposure affects metal halide perovskite (MHP) thin films and perovskite solar cells (PSCs). It examines samples deployed on the Materials International Space Station Experiment (MISSE) 15 and 16 missions. Five methylammonium lead iodide (MAPI) thin films are deployed on MISSE-16, each with distinct UV filters to selectively attenuate AM0 spectral bands. While post-flight optical analysis reveals that the least UV-exposed film exhibits the highest emission and lowest non-radiative recombination rate, no clear correlation is observed among the rest, and all MAPI films maintained excellent integrity throughout the mission. MISSE-15 deployed eight PSCs with diverse structures, MHP compositions, and contact materials. Post-flight analysis reveals stable, highly emissive MHPs, but damaged contacts due to ion migration, which caused loss of electrical response. The MISSE missions demonstrate MHPs' suitability for space applications, while highlighting the need for improved interfacial layers and contact materials to enhance charge carrier mobility, prevent ion migration, and improve charge carrier extraction efficiency.

The advancement of low-earth-orbit (LEO) communication constellations has revitalized interest in Doppler-based positioning. However, conventional Doppler positioning algorithms struggle with dynamic receivers under unknown initial states due to the inherent nonlinearity of the observation model. To address this challenge, we propose an improved least-squares-based algorithm that decouples the estimation of position and velocity, enabling robust positioning from a zero initial state. Simulation results demonstrate that the proposed method achieves meter-level positioning accuracy and decimeter-per-second velocity accuracy under various dynamic scenarios, including high-speed motion. This approach establishes a viable framework for real-time navigation in GNSS-challenged environments using LEO signals.

ABSTRACT Aromatic polyimides (PI) with high resistance to radiation combined with functional graphene‐based fillers are promising materials for a wide range of space applications, such as those involving sensors, antibacterial coatings, and external spacecraft or satellite components. In this work, nanocomposites made of a fluorinated and aromatic polyimide filled with graphene nanoplatelets (GNP) (different concentrations from 5 to 20 wt.%) are prepared following an eco‐friendly approach with a bio‐based solvent, dimethyl isosorbide (DMI), used for the polymer synthesis and the composite processing. Several experimental techniques are used to investigate the morphology and surface properties of the PI/GNP nanocomposites, assessing their potential application in space environments, in particular for low Earth orbit (LEO).

In this paper, we investigate the Adaptive Service Migration (ASM) problem in dynamic satellite edge computing networks, focusing on Low Earth Orbit satellites with time-varying inter-satellite links. We formulate the ASM problem as a constrained optimization problem, aiming to minimize overall service cost, which includes both interruption cost and processing cost. To address this problem, we propose ASM-DRL, a deep reinforcement learning approach based on the soft Actor-Critic framework. ASM-DRL introduces an adaptive entropy adjustment mechanism to dynamically balance exploration and exploitation, and adopts a dual-Critic architecture with soft target updates to enhance training stability and reduce Q-value overestimation. Extensive simulations show that ASM-DRL significantly outperforms baseline approaches in reducing service cost.

The ongoing development of modern telecommunication technologies is leading to a steady increase in electromagnetic pollution on Earth and space. This pollution in Low Earth Orbit (LEO) can impact space-based systems and operations, making it difficult to control small satellites. Furthermore, it can interfere with scientific measurements and experiments conducted in space. The primary objective of this paper is to demonstrate the ability to design and develop a 3-unit PocketQube-class student satellite, MRC-100, as an extension of the SMOG-1 one-unit PocketQube satellite, the fourth satellite of Hungary. The MRC-100 satellite comprises several scientific payloads. The main one is a wide-band spectrum analyzer that operates in the frequency range of 30 MHz to 2.6 GHz and is used to measure electromagnetic pollution in Low Earth Orbit. This paper's measurements were conducted on an extended band ranging from (2–3.1 GHz). We present the capabilities of the extended band spectrum analyzer to measure electromagnetic pollution with the designed system's limited size 40 × 40 mm, weight, and power consumption of less than 400 mW. The working extended band spectrum analyzer was tested on the satellite flight module in the laboratory.

Abstract This paper presents a novel approach for precise orbit determination (POD) of broadband low Earth orbit (LEO) satellites employing Doppler shift measurements using a regional ground station network. Unlike traditional GNSS-based POD methods, our approach leverages the distinctive Doppler signatures generated by the high orbital velocities of LEO satellites, addressing the challenges posed by the signal characteristics and hardware constraints of broadband satellites. We develop a comprehensive mathematical framework for network-based POD and propose three distinct approaches to handle satellite clock synchronization: reference satellite selection, zero-mean constraint, and clock ensemble methods. Using simulated observations from a regional network of 18 continuously operating reference stations tracking Starlink satellites, we demonstrate the theoretical algorithmic potential for significant orbital accuracy improvements under simulation conditions, achieving theoretical upper bounds of mm-level positions (from 15 km initial errors), 10 −9 m/s velocities (from 1.5 km/s initial errors), and 2 × 10 −9 s/s clock drift precision (from 10 −8 s/s initial errors). These improvements translate to an enhancement in Doppler measurement accuracy from 1.5 × 10 3 m/s to 2 × 10 −9 m/s. The clock ensemble approach exhibits superior stability and robustness, though at a higher computational cost. These achievements confirm the theoretical potential of the developed model. Practical implementation is still constrained by hardware limitations, environmental factors, and signal processing complexities, which need further investigation. This research adds to the ongoing research in utilizing broadband LEO satellites for reliable positioning, navigation, and timing, particularly valuable for users where traditional GNSS signals may be compromised or insufficient.

Abstract The growing demand for low-cost, versatile small satellites in Low Earth Orbit (LEO) has significantly increased orbital traffic, amplifying the challenge of sustaining satellite missions without onboard propellant. These satellites are often deployed in orbital regimes where atmospheric Drag and Solar Radiation Pressure (SRP) constitute the main non-conservative forces, often of comparable magnitudes. Non-propulsive control techniques leveraging aerodynamic forces and SRP offer promising alternatives for maintaining and adjusting satellite orbits. This paper introduces a propellant-less steering law that exploits Drag and SRP forces to mitigate orbital decay, optimizing satellite orientation to minimize cumulative deceleration effects. The proposed approach calculates the optimal cross-sectional area for Drag and SRP influences, effectively reducing orbital decay. Applied in simulations to ongoing small satellite missions under simple operational constraints, the method demonstrates notable decay reduction compared to historical mission data. Finally, this paper presents a Flight Envelope that details the potential reductions in orbital decay achievable for various classes of small satellites in LEO, with special emphasis on Very Low Earth Orbit (VLEO) and the transition to higher altitudes. The analysis considers critical parameters including altitude, satellite shape, and orbital geometry. This framework offers vital insights for both mission planning and vehicle design in these challenging orbital regimes.

This paper presents a real-time handover and link assignment framework for low-Earth-orbit (LEO) satellite networks operating in dense urban canyons. The proposed Markov chain-guided simulated annealing (MCSA) algorithm optimizes user-to-satellite assignments under dynamic channel and capacity constraints. By incorporating Markov chains to guide state transitions, MCSA achieves faster convergence and more effective exploration than conventional simulated annealing. Simulations conducted in Ku-band urban canyon environments show that the framework achieves an average user satisfaction of about 97%, providing an approximately 10% improvement over genetic algorithm (GA) results. It also delivers 10–15% higher resource utilization, lower blocking rates comparable to integer linear programming (ILP), and superior runtime scalability with linear complexity O(k·|U|·|S|). These results confirm that MCSA provides a scalable and robust real-time mobility management solution for next-generation LEO satellite systems.

Aerodynamic study of a 3U CubeSat for drag-based in-plane orbital maneuvers in Very Low Earth Orbit

Correlation between ballistic coefficients and natural decay times of space debris in very low Earth orbit

Corrigendum to “Precise formation flying in low earth orbit under environmental and systematic uncertainties” [Acta Astronaut. 235 (2025) 130–140

Plasma source for simulating ionosphere and upper atmosphere environments at low Earth orbits

Ionospheric plasma drag on small satellites in low-earth orbit

After a period of pure governmental space activities, financed by public money, space has become a commercial business with an estimated turnover of 660 billion USD in 2024 and an expected growth of more than 1.5 trillion USD by 2035. Space activities have transferred from national prestige motives to entrepreneurial business motives. This process has been accelerated considerably with what we presently label as the New Space era. Indeed, since the year 2000, we have witnessed a number of changes in space launch approaches as well as a growing number of smallsats, CubeSats, and satellite constellations in Low Earth Orbit. As a result of these space activities becoming affordable to a large range of countries and, at present, having an important effect on STEM education and capacity building particularly in emerging space nations, there is a need to prepare the future workforce for an economy which will considerably be driven by space-based communications and applications. Indeed, there is no reason why countries, over and beyond the traditional major spacefaring nations, should not prepare for this space business era by becoming active players themselves. Various international initiatives such as the US-led Artemis and the Chinese-led ILRS initiatives support this venue and could become a strong catalyst, but an important element is to have a national space strategy implemented stepwise. A template on how to establish such a strategy is provided in this article. A discussion will analyze the rationale and arguments for emerging space nations to become part of this development, suggesting a number of further studies to enhance this approach.

This work introduces a novel microstrip antenna capable of dual-band operation and dual-circular polarization, specifically designed for K/Ka-band applications in small autonomous aerial vehicles (AAVs) and low Earth orbit (LEO) satellites. The antenna incorporates strategically placed arrow-shaped and T-shaped stubs to generate right-hand and left-hand circular polarization in two distinct frequency bands. Through the concurrent excitation of orthogonal modes (TM10/TM01 and TM30/TM21), the stubs enable precise tuning of the resonant frequencies. The geometry of these stubs permits independent adjustment of each band, ensuring optimized performance across multiple frequencies. Experimental validation via a 2 × 2 array prototype operating at 18.6 and 30.8 GHz demonstrates impedance bandwidths of 10.9% and 4.75%, axial ratio bandwidths of 3.65% and 2.25%, and realized gains of 9.35 dBic and 10.65 dBic, respectively. These results confirm the design's suitability for advanced communication systems.

FAST: A battery data recovery method for missing information due to delayed telemetry.

Introduction This work presents an adaptive ant colony (AdCO) framework for dynamic task management in heterogeneous Non-Terrestrial Network–Internet of Things (NTN-IoT) systems integrating Unmanned Aerial Vehicles (UAVs) and Low Earth Orbit (LEO) satellites. The framework addresses key challenges such as stochastic mobility, intermittent connectivity, and latency-sensitive operations common in large-scale IoT deployments. Methods The proposed approach employs adaptive pheromone learning, heuristic control, and multi-timescale scheduling. It follows a hierarchical co-optimization strategy, where UAV swarms perform edge-side task allocation while LEO satellites handle relay scheduling during orbital passes. Event-triggered pheromone resets and distributionally robust cost modeling are introduced to maintain stability and adaptability under dynamic network conditions. Results Simulation results demonstrate superior performance compared to classical Ant Colony Optimization (ACO) and recent meta-heuristic methods. The proposed model achieves higher task completion ratios, reduced end-to-end latency, and enhanced energy-normalized throughput across different orbital configurations, traffic patterns, and link failures. Discussion The findings confirm the efficiency and resilience of the proposed framework in NTN-IoT operations. Its adaptability makes it suitable for critical applications such as disaster response, precision agriculture, and maritime monitoring, where real-time coordination and reliability are essential.

The rapid expansion of Low Earth Orbit (LEO) satellite constellations such as Starlink, OneWeb, and Iridium has created new opportunities for global connectivity while introducing major challenges in orbit prediction, traffic management, and resource allocation. Traditional orbit propagation models (e.g., SGP-4) and physics-informed approaches often fail to meet accuracy requirements due to atmospheric drag, space weather, and orbital heterogeneity. Although machine learning (ML) techniques show strong potential for improving prediction accuracy, their dependence on large, high-quality datasets limits their applicability to new constellations. This paper presents a similarity-based multi-source transfer learning (MSTL) framework that leverages orbital similarities across heterogeneous constellations to enable accurate orbital period prediction with minimal target data. Unlike conventional physics-informed feature engineering, which can degrade performance by up to 461%, our method employs a minimalist feature set (altitude, inclination, and eccentricity) directly extracted from Two-Line Element (TLE) data. Through similarity-driven source selection and filtered multi-source knowledge integration, the proposed framework reduces prediction error by 88.2% (RMSE = 0.045 min, R² = 0.9972) using only 25 labeled samples from the target constellation. The findings show that domain-aware similarity filtering outperforms complex feature engineering, challenging conventional assumptions about transfer learning in physics-based domains. This work offers a scalable, efficient, and practical solution for emerging LEO operators, enabling rapid model development without extensive data collection.

Investigations into human performance and health status during long-duration spaceflights are ongoing aboard the International Space Station (ISS) and are critical for planning missions beyond Low Earth Orbit (LEO). This review evaluates the current evidence on point-of-care-testing (POCT) in space, discussing requirements for POCT to support astronaut health during extended deep space missions and the potential for technology transfer to terrestrial healthcare. Microgravity disrupts biochemical and hormonal regulation, leading to reversible homeostatic dysregulation across multiple organ systems in astronauts during spaceflight in LEO. Missions beyond LEO may significantly increase risks of morbidity and mortality in particular for cardiovascular disease. The ability to assess key organ functions by expanding the range of detectable biomarkers on POCTs is crucial for ongoing health monitoring, urgent clinical decisions, and future mission planning. The recent implementation of high-sensitivity cardiac troponin I on POCT will be essential for early identifying myocardial injury and facilitating telemedicine support. Furthermore, the development and use of reference change values (RCV) in space environment, derived from biomarkers measured longitudinally in real-time onboard, will be crucial to differentiate clinically relevant changes in biomarkers levels from alterations induced by microgravity. This approach may overcome the use of traditional cut-off values which are assessed and generally applied under stable terrestrial conditions. Clinical laboratory capabilities on the ISS are currently minimal. As missions lengthen, and extend beyond LEO, enhanced POCT is needed. Limited data on POCT performance in space highlight the importance of laboratory professionals' involvement to ensure high-quality testing and accurate interpretation.

In order to ensure the sustainability of the space ecosystem, new types of missions are being developed, such as on-orbit servicing missions (OOS) and active debris removal (ADR) missions. The use of OOS and ADR in low-Earth orbits has a great potential. However, their implementation faces significant problems. Only a few successful OOS missions have been launched and operated in recent decades, while ADR missions have not yet been implemented in orbit. Therefore, the study of the problems associated with the justification and preplanning of OOS and ADR missions is important to improving our understanding of these operations and their effectiveness. The implementation of OOS and ADR is closely related to the efficiency of performing a sequence of orbital maneuvering tasks under conditions of limited energy capabilities of the servicer. The values of the efficiency indices for different OOS and ABC routes may differ significantly. Methods for optimizing the routes of multi-purpose OOS and ADR missions have already been developed and are being developed. The existing literature is mainly focused on finding solutions aimed at minimizing the energy consumption of OOS and ADR missions and reducing their total duration because these factors are considered the most significant in mission planning. Much less attention is paid to optimizing OOS and ADR routes based on the flight safety criterion, which significantly affects the cost of mission insurance. This calls for the development of prompt methods for the multicriteria optimization of OOS and ADR routes taking into account the flight safety criterion. The goal of this work is to develop a prompt method for the two-criteria optimization of sequential routes for multi-purpose OOS and ADR missions performed by a servicer with propulsion units of low constant thrust. The problem is formulated as a two-criteria orbital traveling salesman problem. The methods of solving the problem are multicriteria genetic Pareto optimization, averaging of differential equations, and analytical simulation of servicer orbit transfers. The use of a genetic Pareto optimization algorithm made it possible to avoid local optimal solutions and determined the adopted computational costs. A significant reduction in computational costs was also achieved by using analytical simulation of orbit transfers of a servicer with propulsion units of low constant thrust. The novelty of the obtained results lies in the development of a prompt method for the two-criteria optimization of sequential routes of multi-purpose OOS and ADR missions. The method is easily extendable to a larger number of estimation criteria. The results of this work may be used in the justification and preplanning of OOS and ADR missions in low-Earth orbits.