Low Earth Orbit Satellite Research Articles

Single laser based novel wavelength shift keying scheme for ground to satellite bidirectional links

Abstract Laser communication in space is gaining more recognition due to its ability to provide a much broader and unregulated data transmission capacity compared to traditional radio frequency systems, while also significantly decreasing the size, power requirements, and weight of the communication system. In this work, a novel technique for the generation of a wavelength shift keying (WSK) signal for the bidirectional transmission of 10 Gbps data between the ground station and low Earth orbit (LEO) satellite is presented. Our proposed scheme requires a single laser source to transmit WSK signal, that generally requires two wavelength sources to transmit the binary data bits. Furthermore, the scheme allows us to remodulate the optical signal received at the LEO satellite for downlink signal transmission. Therefore, the requirement of a laser source at the LEO satellite is eliminated, achieving the much desirable goals of low power consumption, weight and cost. The free space optical (FSO) channel is modelled using the gamma-gamma channel model. The performance of the proposed link is also compared with a conventional On-Off keying (OOK) based modulation scheme by using bit-error-rate (BER) as the performance metric.

Quantifying the Environmental Impacts of Manufacturing Low Earth Orbit (LEO) Satellite Constellations

Quantifying the Environmental Impacts of Manufacturing Low Earth Orbit (LEO) Satellite Constellations

Utility optimization for computation offloading and splitting in time-varying HAP and LEO satellite integrated MEC networks

To provide ubiquitous and low-latency communication and computation services for remote and disaster areas, high altitude platform (HAP) and low earth orbit (LEO) satellite integrated multi-access edge computing (HLS-MEC) networks have emerged as a promising solution. However, most current studies directly assume that the number of connected satellites is fixed and neglect the modeling of the time-varying multi-satellite computing process. Motivated by this, we establish an M/G/K(t) queuing model to illustrate task computation on satellites. To evaluate the efficiency and quality of computation offloading and splitting, we develop a utility model. This model is defined as a difference between a value function that assesses the trade-offs of task offloading, considering latency reductions and energy savings, and a cost function that quantifies expenses related to latency and energy consumption. After formulating the utility maximization problem, we propose the deep reinforcement learning-based offloading and splitting (DBOS) scheme that can overcome the time-varying uncertainties and high dynamics in the HLS-MEC network. Specifically, the DBOS scheme can learn the best computation offloading and splitting policy to maximize the utility by sensing the number of connected satellites, the distance between the HAP and satellites, the available computing resources, and the task arrival rate. Finally, we evaluate and validate the computational complexity and convergence property of the DBOS scheme. Numerical results show that the DBOS scheme outperforms the other three benchmarks and maximizes the utility under time-varying dynamics.

Inter-beam handover schemes for LEO satellites in 5G satellite–terrestrial integrated networks

Unlike terrestrial handover schemes, the handover schemes in 5G satellite–terrestrial integrated network (STIN) face several challenges, such as large propagation delay, complex channel environment, and fast satellite movement. Therefore, the handover schemes designed in the 5G terrestrial network is not suitable for the 5G STIN. In view of this, this paper considers the inter-beam handover problem for the 5G STIN with a low earth orbit satellite and a ground user. We establish the satellite channel model, which includes path loss, rain attenuation, and multi-beam antenna gain. To model the mobile feature of the user, we consider a two-dimensional random walk model. Then, we propose A5 event-based conditional handover (CHO) scheme, time factor-based CHO scheme, and load factor-based CHO scheme to achieve efficient inter-beam handover. Considering that there may be multiple beams that meet the triggering condition in each handover scheme, we also propose three kinds of beam selection schemes, namely random beam selection scheme, maximum power-based beam selection scheme, and minimum distance-based beam selection scheme. To evaluate the performance of the proposed handover schemes, key performance indicators, such as handover frequency, ping-pong handover rate, unnecessary handover rate, handover failure rate, and average transmission rate are analyzed. Simulation results verify the superiority of the proposed handover schemes by comparing them with the benchmark scheme.

Enhancing Satellite Link Security Against Drone Eavesdropping Through Cooperative Communication

ABSTRACTIntegrated satellite terrestrial networks (ISTNs) are emerging as a promising next‐generation communication technology, for example, B5G and 6G, with low‐earth orbit (LEO) satellites playing a growing role. However, the complex and unique characteristics of ISTNs make them more susceptible to cyberattacks. Recently, the use of drones for public and private services has increased the risk of eavesdropping on LEO satellite links. Such scenario presents an extremely challenging environment due to dynamic nature of LEO satellite and drone along with atmospheric attenuation at sub‐THz frequencies. This study proposes a novel adaptive power‐bandwidth cooperative scheme designed to mitigate the likelihood of eavesdropping attacks on LEO satellite links communicating with a ground station when a drone is within the line of sight. The mathematical algorithm dynamically adapts the resources to maximize the normalized secrecy capacity in this challenging scenario while maintaining a reasonable signal‐to‐noise ratio (SNR) at the legitimate receiver. The adaptive scheme involves strategic cooperation with a nearby terrestrial third party to amplify and forward the satellite signal to the ground station receiver. The simulation results demonstrate the effectiveness of the proposed algorithm, showing significant improvements (> 70%) compared to the non‐adaptive scheme over a wide range of elevation angles.

Ionospheric TEC and its irregularities over Egypt: a comprehensive study of spatial and temporal variations using GOCE satellite data

Abstract This study delves into ionospheric characteristics during solar cycle 24 using data from the Global Positioning System (GPS) and Low Earth Orbit (LEO) satellites, GOCE. The present study fills the gap of not assessing and studying GOCE satellite data before in Egypt. Focusing on spatial and temporal variations of ionospheric Total Electron Content (TEC) over Egypt and the Middle East across a 4-year dataset, monthly average Vertical Total Electron Content (VTEC) variations are scrutinized, emphasizing extremes during heightened and reduced solar and geomagnetic activities. Results TEC typically decreases with latitude’s increase, with peak ionization during equinoxes and troughs during solstices. Notably, VTEC values consistently reach maximum values on days of heightened solar and geomagnetic activities. GOCE data is evaluated against International Reference Ionosphere (IRI) model and NeQuick2 model by selecting 10 days from all data by using a statistical comparison via t-tests. There is not significant difference between them except for two days between GOCE-IRI. The values of Root Mean Square Error (RMSE) are 3.7403 and 4.4655 for GOCE – NeQuick2 model and GOCE – IRI model, respectively. Ionospheric scintillation, signifying rapid electron density fluctuations, is assessed through amplitude scintillation index (S4), S4 proxy, and Rate Of TEC Index (ROTI). A robust correlation between S4 and S4 proxy is noted, thus scintillation can be studied by using S4 proxy instead of S4. Temporal variations indicate heightened scintillation during geomagnetic storms and peak solar activity, contrasting with reduced activity during solar minimum. Throughout the study period the maximum scintillation index values for ROTI, S4, and S4 proxy are 0.3, 0.15, and 0.05, indicating minimal scintillation. This comprehensive analysis, rooted in GOCE data, illuminates spatial and temporal dynamics of ionospheric TEC and elucidates ionospheric scintillation characteristics in the Egypt region. These findings are crucial for refining ionospheric models, improving scintillation prediction, and enhancing satellite communication and navigation systems, especially in the study region.

Decision Transformer-Based Efficient Data Offloading in LEO-IoT.

Recently, the Internet of Things (IoT) has witnessed rapid development. However, the scarcity of computing resources on the ground has constrained the application scenarios of IoT. Low Earth Orbit (LEO) satellites have drawn people's attention due to their broader coverage and shorter transmission delay. They are capable of offloading more IoT computing tasks to mobile edge computing (MEC) servers with lower latency in order to address the issue of scarce computing resources on the ground. Nevertheless, it is highly challenging to share bandwidth and power resources among multiple IoT devices and LEO satellites. In this paper, we explore the efficient data offloading mechanism in the LEO satellite-based IoT (LEO-IoT), where LEO satellites forward data from the terrestrial to the MEC servers. Specifically, by optimally selecting the forwarding LEO satellite for each IoT task and allocating communication resources, we aim to minimize the data offloading latency and energy consumption. Particularly, we employ the state-of-the-art Decision Transformer (DT) to solve this optimization problem. We initially obtain a pre-trained DT through training on a specific task. Subsequently, the pre-trained DT is fine-tuned by acquiring a small quantity of data under the new task, enabling it to converge rapidly, with less training time and superior performance. Numerical simulation results demonstrate that in contrast to the classical reinforcement learning approach (Proximal Policy Optimization), the convergence speed of DT can be increased by up to three times, and the performance can be improved by up to 30%.

An improved analytical method for rarefied aerothermodynamics on a complex geometry in free-molecular flows

A numerical method for high altitude aerothermodynamic analysis code for Very Low Earth Orbit (VLEO) satellite and spacecraft, named as HACS, is presented in this article. HACS is a computational tool that addresses the challenges by integrating the free-molecular gas kinetic model with novel particle sampling method and robust particle tracing algorithm to predict the shadow region on surfaces. To ensure the reliability and accuracy of the HACS, a rigorous verification and validation process has been systematically conducted by comparing the aerothermodynamic properties of forces, moments, and heat flux with the direct simulation Monte-Carlo (DSMC) results. The HACS is applied to the realistic geometries of VLEO satellite, the Apollo re-entry module, and spacecraft including fin and wing shapes. Results demonstrate that HACS provides the aerothermodynamic properties within the time frame of 60 seconds for the complex geometries and the accuracy of the HACS is guaranteed above 120 km altitude. The maximum relative error of the aerothermodynamic properties is less than 5% compared to the DSMC results at the lowest altitude of about 120 km, and has smaller relative errors as the altitude increases.

Orbit Determination Method for BDS-3 MEO Satellites Based on Multi-Source Observation Links

Research on augmentation and supplement systems for navigation systems has become a significant aspect in comprehensive positioning, navigation and timing (PNT) studies. The BeiDou-3 navigation satellite system (BDS-3) has constructed a dynamic inter-satellite network to gain more observation data than ground monitoring stations. Low Earth orbit (LEO) satellites have advantages in their kinematic velocity and information carrying rate and can be used as satellite-based monitoring stations for navigation satellites to make up for the distribution limitation of ground monitoring stations. This study constructs multi-source observation links with satellite-to-ground, inter-satellite and satellite-based observation data, proposes an orbit synchronization method for navigation satellites and LEO satellites and verifies the influence thereof on orbit accuracy with different observation data. The experimental results under conditions of real and simulated observation data showed the following: (1) With the support of satellite-based observation links, the orbit accuracy of the BDS-3 MEO satellites could be improved significantly, with a 78% improvement with the simulation data and a 76% improvement with the real data. When the navigation satellites leave the monitoring area of the ground monitoring stations, the accuracy reduction tendency of the orbit prediction could also be slowed down with the support of the LEO satellites and the accuracy could be maintained within centimeters. (2) Comparing the orbit accuracy with the support of the satellite-to-ground observation links, the orbit accuracy of the MEO satellites could be improved by 65.5%, 73.7% and 79.4% with the support of the 6, 12 and 60 LEO satellites, respectively. When the observation geometry and the covering multiplicity meet the basic requirement of orbit determination, the improvements to the orbit accuracy decrease with the growth of LEO satellite numbers. (3) The accuracy of orbit determination with the support of the LEO satellites or the inter-satellite links was at the centimeter level for both, verifying that inter-satellite links and satellite-based links can be used as each other’s backups for navigation satellites. (4) The accuracy of orbit determination with the multi-source observation links was also at the centimeter level, which was not better than the results with the support of the satellite-to-ground and inter-satellite links or the satellite-to-ground and satellite-based links.

Robustness of LEO satellite hypernetworks under different network topologies and attack strategies

The development of low earth orbit (LEO) satellites has become a crucial and essential component with the advancement of digitalization. However, LEO satellites also face various security challenges within their networks, and the failure of certain satellites may trigger cascading failures. To gain a deeper understanding of cascading failure process in LEO satellite networks and enhance its robustness, this letter proposes a novel satellite network model by combining complex network and hypernetwork theories. By altering the network structure and model parameters, the robustness performance of the LEO satellite network under three types of attacks and two different load distribution methods is thoroughly investigated. The results indicate that satellite networks with varying structures are distinct and exhibit different robustness characteristics under specific attack types. Furthermore, the robustness of satellite networks in multiple attack scenarios can be significantly enhanced by implementing improved load allocation strategies. These findings not only provide a theoretical foundation for the design and optimization of satellite networks but also ignite new perspectives and ideas for future research on their robustness.

LEO satellite clock modeling and its benefits for real-time LEO PPP timing

In the kinematic Precise Orbit Determination (POD) process for low earth orbit (LEO) satellites, a significant correlation exists between the orbital and clock parameters. Here, a LEO satellite clock model is proposed to enhance the Precise Point positioning (PPP) timing and time synchronization during the LEO orbit/clock determination. The GRACE-FO satellite was utilized to achieve PPP timing and time transfer for LEO satellites with the real-time (RT) products provided by three analysis centers, namely Centre National d’Etudes Spatiales (CNES), GMV Aerospace and Defense (GMV), and Wuhan Technical University (WHU). For the frequency stability of the PPP timing for LEO satellites, the short-term stability (1280 s) is about 10−13 level, and the long-term stability (10,240 s) is about 10−14 level. Compared with the traditional PPP method (Scheme1), the LEO satellite clock model (Scheme2) is capable of significantly reducing the noise, regardless of whether it is PPP timing or PPP time synchronization. The frequency stability of Scheme 1 shows an improvement in short-term stability (1280 s) by about 8 %-72 % and the max improvement of the long-term stability (10240 s) by approximately 39 %, the result also shows a better improvement in LEO time synchronization.

UAV clusters information geometry fusion positioning method with LEO satellite system

The existing Low-Earth-Orbit (LEO) positioning performance cannot meet the requirements of Unmanned Aerial Vehicle (UAV) clusters for high-precision real-time positioning in the Global Navigation Satellite System (GNSS) denial conditions. Therefore, this paper proposes a UAV Clusters Information Geometry Fusion Positioning (UC-IGFP) method using pseudo-ranges from the LEO satellites. A novel graph model for linking and computing between the UAV clusters and LEO satellites was established. By utilizing probability to describe the positional states of UAVs and sensor errors, the distributed multivariate Probability Fusion Cooperative Positioning (PF-CP) algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster. Criteria to select the centroid of the cluster were set. A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory, which overcomes the discontinuity problem caused by the change of cluster centroids. Finally, the UC-IGFP method achieves the LEO continuous high-precision positioning of UAV clusters. The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster. It significantly improves the accuracy and reliability of LEO-UAV cluster positioning. The results of comprehensive simulation experiments show that the proposed method has a 30.5% improvement in performance over the mainstream positioning methods, with a positioning error of 14.267 m.

Analysis of multipath effects on Low Earth Orbit navigation satellites

Abstract With the large-scale emergence of Low-Earth Orbit (LEO) internet constellations, the direct or indirect utilization of LEO communication constellations for navigation and positioning has become a hot topic of current research. However, the multipath effect remains a critical factor influencing positioning accuracy. Compared to traditional Medium-Earth Orbit (MEO) satellites, LEO satellites move swiftly, resulting in faster multipath variations, which renders traditional multipath envelope analysis methods inapplicable. This study proposes a novel analytical model tailored to the multipath effect characteristics of LEO satellites. Through this model, we have observed that the multipath variations of high-frequency signals in LEO rapidly fluctuate near zero, offering the potential to reduce errors through smoothing methods. Furthermore, the study reveals that the impact of the multipath effect is positively correlated with orbital altitude and inversely correlated with carrier frequency. This study provides a new perspective for understanding the multipath effect characteristics of LEO satellites and offers necessary theoretical support and practical guidance for improving the accuracy of navigation and positioning systems based on LEO satellites. Future research can further explore multipath suppression methods and promote the widespread application of LEO satellites in the field of navigation and positioning.

Based on coverage evaluation design method study of factor low-orbit infrared remote sensing constellation configuration

Abstract To satisfy the infrared detection coverage demands of Low Earth Orbit (LEO) satellites in global missile surveillance, we have devised a comprehensive evaluation system for global missile infrared remote sensing coverage performance. By referencing Walker’s extensive and uninterrupted global coverage constellation layout, we conducted a thorough analysis of various constellation configuration parameters. This analysis aimed to assess the coverage efficiency of differently configured LEO networking satellites. Following a detailed comparative analysis, we settled on an LEO infrared remote sensing constellation configuration featuring an orbit height of 1150 km and an orbit inclination of 60°. After an in-depth examination of the capabilities of the infrared remote sensing constellation and the characteristics of the detection zone, we constructed a Blind Spot Compensation Constellation. This was achieved by integrating four additional LEO satellites with a 0° orbit inclination to bolster coverage in low-latitude regions. Using our comprehensive coverage evaluation system, we rigorously evaluated the ground coverage capabilities of multiple constellations. Notably, the Blind Spot Compensation Constellation achieved impressive coverage, reaching 100%, and excelled particularly in the latitude belt of 20° or less. Although the Original Constellation performed better in the 40° latitude belt compared to the Blind Spot Compensation Constellation, it showed some deficiencies in coverage at a 50 km altitude. Specifically, it averaged 18.417 gaps per day, with a coverage rate slightly below 100%. However, it achieved full coverage at other altitudes. To validate our findings, we conducted scenario simulations. For missile targets, the Original Constellation offered a maximum coverage multiplicity of 6, with a total access duration of 4539.1 seconds. On the other hand, the Blind Spot Compensation Constellation boasted a maximum coverage multiplicity of 8, with a total access duration of 5465.9 seconds. Importantly, both constellations fully covered the missile’s entire 1056-second lifecycle, showcasing commendable performance. In conclusion, the LEO infrared remote sensing constellation and its complementary counterpart, developed and rigorously tested in this study, not only meet the demands of continuous global detection but also cater to the priority detection needs of diverse geographical regions.

Multi-round decentralized dataset distillation with federated learning for Low Earth Orbit satellite communication

Satellite communication and Low Earth Orbit (LEO) satellites are important components of the 6G network, widely used for Earth observation tasks due to their low cost and short return period, making them a key technology for 6G network connectivity. Due to limitations in satellite system technology and downlink bandwidth, it is not feasible to download all high-resolution image information to ground stations. Even in existing federated learning (FL) methods, sharing well-trained parts of the model can still bottleneck with increasing model size. To address these challenges, we propose a new federated learning framework (FL-M3D) for LEO satellite communication that employs multi-round decentralized dataset distillation techniques. It allows satellites to independently extract local datasets and transmit them to ground stations instead of exchanging model parameters. Communication costs depend only on the size of the synthesized dataset and do not increase with larger models. However, the heterogeneity of satellite datasets can lead to sample ambiguity and decreased model convergence speed. Therefore, we propose distilling the datasets to mitigate the negative effects of data heterogeneity. Through experiments using real-world image datasets, FL-M3D reduces communication volume in simulated satellite networks by approximately 49.84% and achieves improved model performance.

Research on Design and Staged Deployment of LEO Navigation Constellation for MEO Navigation Satellite Failure

Low Earth orbit (LEO) satellites have unique advantages in navigation because of their high signal intensity and rapid geometric changes in a short period. In order to solve the problem of constellation performance degradation after a potential failure pertaining one or more medium Earth orbit (MEO) navigation satellites, this paper designs the LEO navigation constellation and considers the task requirements of different stages of constellation deployment. Firstly, the LEO navigation constellation is designed by a non-dominated sorting genetic algorithm II (NSGA-II). The average position dilution of precision (PDOP) is 1.676, which is an improvement compared to the average PDOP offered by the four traditional GNSS. Secondly, the staged deployment of constellation takes into account the degradation of constellation performance caused by the failure of MEO navigation satellites, and the Monte Carlo method is used to analyze the case of three simultaneous satellite failures. The results show that a single satellite failure within each orbital plane and adjacent satellites with close phase separation has a great impact on the performance of the MEO navigation constellation. On this basis, a staged deployment strategy was adopted in order to balance cost, risk, and performance. The three phases deploy 66, 156, and 288 satellites, respectively; as a make-up constellation under contingencies, a navigation enhancement constellation, and an independent navigation constellation, the deployment of the staged sub-constellations meets the mission requirements. The constellation design and staged deployment method proposed in this paper can provide reference for the future study of LEO navigation constellations.

Research on AIS algorithm based on factor graph inference in Doppler localization

Abstract In this paper, an adaptive incremental smoothing (AIS) algorithm based on factor graph inference is proposed to solve the problem of improving the Doppler positioning accuracy of low-Earth orbit communication satellites. Traditional methods such as iterative least squares (ILS) algorithm and Extended Kalman filter (EKF) have certain limitations in real-time Doppler localization. The AIS algorithm uses factor graph inference to identify interference factors, and adopts adaptive smoothing to reduce the impact of estimation errors and promote adaptive noise estimation. The ground station Starlink satellite constellation static positioning was taken as an example, and the simulation was carried out on the STK software simulation platform to verify the feasibility and effectiveness of the algorithm. The experimental results show that the positioning accuracy of the AIS algorithm based on factor graph inference is significantly improved compared with the ILS and EKF algorithms in real-time Doppler positioning solutions. The aim of this research is to improve the positioning accuracy of low-orbit satellites and provide a reference for practical applications.

Upscaling Land Surface Fluxes Through Hyper Resolution Remote Sensing in Space, Time, and the Spectrum

AbstractNumerous efforts to measure land surface fluxes, from leaf to canopy scales, have significantly advanced the field of biogeoscience. However, upscaling these estimates to larger spatial and temporal scales remains a challenge. Recent advancements in remote sensing provide new opportunities to bridge these gaps in upscaling efforts. In this review, I propose that emerging satellite data can support the robust upscaling of land surface fluxes in terms of space through constellations of low Earth orbit satellites, in time through geostationary satellites, and in spectrum via optical, thermal, and microwave satellites. Lastly, I recommend the development of a long‐term network integrating tower‐based hyperspectral, thermal, and microwave instruments to rigorously evaluate the upscaling process of land surface fluxes.

Beacon-Based Uplink Transmission for LoRaWAN Direct to LEO Satellite Internet of Things

Direct-to-satellite IoT (DtS-IoT) communication structure is a promising solution to provide connectivity and extend the coverage of traditional low-power and long-range technologies, especially for isolated and remote areas where deploying traditional infrastructure is impracticable. Despite their bounded visibility, the Low Earth Orbit (LEO) satellites complement the terrestrial networks, offering broader gateway coverage and terrestrial network traffic offloading. However, the dynamics of LEO and the nature of such integration come with several challenges affecting the efficacy of the network. Therefore, this paper proposes Beacon-based Uplink LoRaWAN (BU-LoRaWAN) to enhance satellite-terrestrial communication efficiency. The proposed scheme exploits the LoRaWAN class B synchronization mechanism to provide efficient uplink transmission from LoRaWAN devices placed on the ground to satellite gateways. BULoRaWAN proposes an uplink transmission slot approach to synchronize ground devices’ uplink traffic with LEO-based orbiting gateways. It also uses a queue data structure to buffer end devices’ ready-to-send packets until the appropriate moment. BU-LoRaWAN avoids possible transmission collision by optimizing a random transmission slot for an end device within the beacon window. The proposed system is implemented and evaluated using OMNeT++ network simulator and FLoRaSat framework. The result demonstrates the feasibility of the proposed system. BU-LoRaWAN achieves better performance compared to the standard LoRaWAN, which manages to deliver almost double the traffic delivered by the standard one.

Distributed Observer for Linear Systems with Multirate Sampled Outputs Involving Multiple Delays

This paper focuses on the design of a continuous distributed observer for linear systems under multirate sampled output measurements involving multiple delays. It is mathematically proved that the continuous distributed observer can achieve estimation in a sensor network environment, where output measurements from each sensor are available at different sampling instants, whether these times are periodic or aperiodic, and despite the presence of multiple time-varying delays. Each sampled and delayed measurement represents a node of the network, necessitating a dedicated observer for each node, which has access to only part of the system’s output and communicates with its neighbors according to a given network graph. The exponential convergence of the error dynamics is ensured by Lyapunov stability analysis, which accounts for the influence of the sampled and delayed measurements at each node. To demonstrate the effectiveness of the proposed observer, simulation tests were conducted on the tracking control of chasing satellites in low Earth orbit (LEO), encompassing both small and large sampling rates and delays. The continuous distributed observer with sampled output measurements exhibited convergence in scenarios with different sampling intervals, even in the presence of time-varying delays, achieving asymptotic omniscience, as demonstrated in the convergence analysis.