Geostationary Earth Orbit Satellites Research Articles

Ionospheric behaviors and characteristics in Asian sector during the April 2023 geomagnetic storm with multi-instruments observations

Geomagnetic storms frequently affect satellite navigation, communication and satellite orbits. Monitoring and understanding the ionospheric disturbances and responses to geomagnetic storms are crucial. The detailed ionospheric responses and physical mechanisms to various geomagnetic storms, however, have not yet been extensively studied. In this paper, the ionospheric variation behaviors and features following the April 2023 magnetic storm along the Asian sector are thoroughly studied using multi-instrument observation data, including the Global Navigation Satellite System (GNSS), ionosonde, and other satellites. Large-scale Traveling Ionospheric disturbances (LSTIDs) are observed from BeiDou Geostationary Earth Orbit (GEO) satellites, GPS and GLONASS. LSTIDs traveled with a speed of 760–1300 m/s from high latitude region to low latitude region with a period of about 40 min. The equatorial propagating LSTIDs were generated by coronal mass ejections (CMEs), which occurred in April 2023 with periodic energy input from the auroral area. The poleward LSTIDs are also observed with a velocity of approximately 600–750 m/s and the period is similar. Neutral wind also influenced the characteristics of the ionospheric response. The [O]/[N2] ratio declined during the storm, which led to the formation of the negative storm phases. The largest vertical total electron content (VTEC) is found, and the strengthened region of TEC is mainly centered between ± 20° within geographical latitude. Equatorial Ionospheric Anomaly (EIA) is also observed, which is probably influenced by the electric field. As the time goes on, the peak on the south side of the EIA is disappearing. Meanwhile, the height of the ionospheric maximum electron density rises, and the electron density falls.

A Study on Anti-Jamming Algorithms in Low-Earth-Orbit Satellite Signal-of-Opportunity Positioning Systems for Unmanned Aerial Vehicles

Low-Earth-Orbit (LEO) satellite Signal-of-Opportunity (SOP) positioning technology has gradually matured to meet the accuracy requirements for unmanned aerial vehicle (UAV) positioning in daily scenarios. Advancements in miniaturization technology for positioning terminals have also made this technology’s application to UAV positioning crucial for UAV development. However, in the increasingly complex electromagnetic environment, there remains a significant risk of degradation in positioning performance for UAVs in LEO satellite SOP positioning due to unintentional or malicious jamming. Furthermore, there is a lack of in-depth research from scholars both domestically and internationally on the anti-jamming capabilities of LEO satellite SOP positioning technology. Due to significant differences in the downlink signal characteristics between LEO satellites and Global Navigation Satellite System (GNSS) signals based on Medium Earth Orbit (MEO) or Geostationary Earth Orbit (GEO) satellites, the anti-jamming research results of traditional satellite navigation systems cannot be directly applied. This study addresses the narrow bandwidth and high signal-to-noise ratio (SNR) characteristics of signals from LEO satellite constellations. We propose a Consecutive Iteration based on Signal Cancellation (SCCI) algorithm, which significantly reduces errors during the model fitting process. Additionally, an adaptive variable convergence factor was designed to simultaneously balance convergence speed and steady-state error during the iteration process. Compared to traditional algorithms, simulation and experimental results demonstrated that the proposed algorithm enhances the effectiveness of jamming threshold settings under narrow bandwidth and high-power conditions. In the context of LEO satellite jamming scenarios, it improves the frequency-domain anti-jamming performance significantly and holds high application value for drone positioning.

Multiband photometric observations of GEO objects through Sloan filters

With the precipitous growth of the population of objects in Earth's orbit, all major space agencies and companies have made space surveillance a priority to ensure the safety of space missions. With the application of the methods of space surveillance, this article aims to characterize the population of objects in the Geostationary Earth Orbit (GEO) using optical measurements across multiple spectral bands. The study takes place in a context in which the existence of space debris poses a continuous hazard to the operations of active satellites in GEO. Photometric observations of GEO objects using Sloan filters were obtained with SCUDO, a small-aperture telescope part of the Sapienza network. Observations are divided into categories, including 11 objects: rocket bodies (4), defunct satellites (3), and active satellites (4). The spectral response of these objects has been analyzed leading to the identification of a photometric signature which was repeated for two Eutelsat satellites observed under same conditions. All the observed targets resulted in a lower magnitude in the near-infrared. Color indexes also indicate that they are redder than the Sun. This is particularly evident for SL-12 rocket bodies, whose g’-z’ reaches 1.5.

Comparison of the SRP spherical model between LEO and GEO satellites

Solar Radiation Pressure (SRP) is a phenomenon caused by the pressure exerted by solar photons on a satellite’s surface when it is exposed to sunlight. It is a form of radiation force and can significantly impact the motion and behaviour of satellites in space. SRP influences a satellite’s orbit by causing changes in its semimajor axis, eccentricity, inclination, argument of perigee, right ascension of the ascending node, and mean anomaly. SRP models are used to simulate the effects of solar radiation pressure on satellites. These models are essential for accurately predicting satellite trajectories and orbital behaviour. There are several types of SRP models, such as spherical model, flat model, box-wing model, faceted model, and analytical SRP models. This research focuses on Telkom 1 and LAPAN A1 satellites, both belonging to Indonesia and positioned in Geostationary Earth Orbit (GEO) and Low Earth Orbit (LEO) orbits, respectively. The study aims to find a comparison of the effects of SRP spherical model on LEO and GEO satellites. Our modelling shows that the semimajor axis and eccentricity are sensitive to SRP, while the inclination and right ascension of the ascending node are not significantly affected. Comparing the effects of SRP on LEO and GEO satellites, we concluded that both LEO and GEO orbit experience the most significant fluctuations in January (perihelion), likely due to the influence of solar radiation pressure.

Real-time high-precision baseline measurement of satellite formation flying based on GNSS

With the establishment of the Chinese space station, a series of space science missions will be conducted in its vicinity. One of the extended tasks for the in-orbit service of space station is the formation flying of small satellites centered around the space station. Satellite formations can perform simultaneous three-dimensional observations of the space station, generating three-dimensional images and monitoring and assessing the status of critical components of the space station. The real-time and accurate relative position measurement is one of the key issues in formation flying. It is a fundamental prerequisite for maintaining and reconfiguring formation configurations, collision avoidance and safety assurance. GNSS-based relative positioning is a low-cost and high-precision measurement method, which is not constrained by light, weather, or relative attitude of satellites. This study introduces a novel approach to determine the relative position of satellites based on single-epoch Global Navigation Satellite System (GNSS) carrier phase difference measurements. Unlike traditional methods, the proposed technique eliminates the need for precise ephemeris and clock bias files and does not require historical observation data. The algorithm avoids the complexity associated with full cycle ambiguity jumps, facilitating real-time, high-precision calculations of relative position baseline vectors. Special attention is given to the influence of Geostationary Earth Orbit (GEO) satellites in the BeiDou Navigation Satellite System (BDS), and measures are taken to mitigate their impact on measurement accuracy by adjusting their observation weights. Our newly developed GNSS-based real-time measurement module, designed for high-quality GNSS signal reception and data communication, was tested on terrestrial and simulated low-orbit platforms. Remarkably, over baselines ranging from 10 m to 9.3 km, while traditional pseudorange differential measurements showed errors up to 1.5571 m, our proposed method consistently held errors under 5 cm and ensured computational speeds within 0.1 s per epoch. High-dynamic zero-baseline tests further validated its potential, with errors less than 1 cm. The innovations encapsulated in this work, resonating with the evolving trends of miniaturized and scalable satellites, present a cost-efficient and real-time solution for inter-satellite relative position measurement. This promises a new horizon in satellite formation technology, with future endeavors focusing on on-orbit experiments.

Data formats and standards for opportunistic rainfall sensors.

Opportunistic sensors are increasingly used for rainfall measurement. However, their raw data are collected by a variety of systems that are often not primarily intended for rainfall monitoring, resulting in a plethora of different data formats and a lack of common standards. This hinders the sharing of opportunistic sensing (OS) data, their automated processing, and, at the end, their practical usage and integration into standard observation systems. This paper summarises the experiences of the more than 100 members of the OpenSense Cost Action involved in the OS of rainfall. We review the current practice of collecting and storing precipitation OS data and corresponding metadata, and propose new common guidelines describing the requirements on data and metadata collection, harmonising naming conventions, and defining human-readable and machine readable file formats for data and metadata storage. We focus on three sensors identified by the OpenSense community as prominent representatives of the OS of precipitation: Commercial microwave links (CML): fixed point-to-point radio links mainly used as backhauling connections in telecommunication networks Satellite microwave links (SML): radio links between geostationary Earth orbit (GEO) satellites and ground user terminals. Personal weather stations (PWS): non-professional meteorological sensors owned by citizens. The conventions presented in this paper are primarily designed for storing, handling, and sharing historical time series and do not consider specific requirements for using OS data in real time for operational purposes. The conventions are already now accepted by the ever growing OpenSense community and represent an important step towards automated processing of OS raw data and community development of joint OS software packages.

The Analysis of Ionospheric TEC Anomalies Prior to the Jiuzhaigou Ms7.0 Earthquake Based on BeiDou GEO Satellite Data

The position between BeiDou geostationary Earth orbit (GEO) satellites and ground-based receiving stations can roughly be considered to be constant with negligible fluctuations; thus, the total electron content (TEC) data over a fixed ionospheric piercing point (IPP) can be continuously acquired, which is advantageous for monitoring ionospheric disturbances. Focused on the Jiuzhaigou Ms7.0 earthquake that occurred on 8 August 2017, the TEC data inverted by the BeiDou GEO satellite were analyzed to extract ionospheric disturbances potentially associated with the earthquake. It was found that significant anomalies in ionospheric TEC occurred 10–11 days, 6–7 days, and 1–9 h prior to the earthquake, which was mainly located in the southeast and southwest directions within about 2500 km distance from the epicenter. Comparing the spatial and temporal characteristics between the ionospheric disturbance and the radon gas near the surface, the atmospheric electric field, and the spectrum of TEC data, it was considered that the chemical and acoustic–gravity wave pathway may play an important role in the lithosphere–atmosphere–ionosphere coupling (LAIC) mechanism.

On the Importance of a Geostationary View for Tropical Cloud Feedback

AbstractThis study shows that geostationary satellites are critical to estimate the accurate cloud feedback strength over the tropical western Pacific (TWP). Cloud feedback strength was calculated by the simultaneous relation between cloud cover and sea surface temperature (SST) over the TWP [120°E–170°E, 20°S–20°N]. During 2011–2018, the cloud cover was obtained by geostationary earth orbit satellite (GEO) and low‐level earth orbit satellite (LEO) (AGEO, ALEO), and the NOAA's all‐sky SST (To) was weighted with the clear‐sky fraction observed by GEO and LEO (TwGEO; TwLEO). The linear regression coefficients between clouds and SST are very different: −7.93%K−1 (AGEO/TwGEO), −6.94%K−1 (ALEO/TwGEO), −1.35%K−1 (AGEO/TwLEO), −0.69%K−1 (ALEO/TwLEO), −0.02 %K−1 (AGEO/To), and −0.50 %K−1 (ALEO/To). Among these, only the TwGEO values provided a valid cloud feedback signal. This is because GEO's field of view is large enough to simultaneously capture cloud cover over the entire TWP.

Modeling and analysis for reaction control thruster used for station-keeping maneuvers of a GEO satellite

This paper introduces a theoretical description, force, and torque analysis of a Reaction Control Thruster (RCT) used as an actuator in Attitude Determination and Control Subsystem (ADCS). Mathematical formalization, realization, and implementation are offered to implement the RCT model using Matlab-Simulink. Furthermore, this paper proposes an accurate RCT Simulink model to control the orientation and stabilizes the Geostationary Earth Orbit (GEO) satellite within its orbit. Finally, a comparative analysis is carried out with an existing satellite platform (Eurostar-3000) based on the Root Mean Square Error (RMSE) for the delta velocity (delta-𝒱) parameter. The outcomes of the model simulation validated the effectiveness of the proposed approach.

Rate Splitting Multiple Access for Next Generation Cognitive Radio Enabled LEO Satellite Networks

Low Earth Orbit (LEO) satellite communication (SatCom) has drawn particular attention recently due to its high data rate services and low round-trip latency. It has low launching and manufacturing costs than Medium Earth Orbit (MEO) and Geostationary Earth Orbit (GEO) satellites. Moreover, LEO SatCom has the potential to provide global coverage with a high-speed data rate and low transmission latency. However, the spectrum scarcity might be one of the challenges in the growth of LEO satellites, impacting severe restrictions on developing ground-space integrated networks. To address this issue, cognitive radio and rate splitting multiple access (RSMA) are the two emerging technologies for high spectral efficiency and massive connectivity. This paper proposes a cognitive radio enabled LEO SatCom using RSMA radio access technique with the coexistence of GEO SatCom network. In particular, this work aims to maximize the sum rate of LEO SatCom by simultaneously optimizing the power budget over different beams, RSMA power allocation for users over each beam, and subcarrier user assignment while restricting the interference temperature to GEO SatCom. The problem of sum rate maximization is formulated as non-convex, where the global optimal solution is challenging to obtain. Thus, an efficient solution can be obtained in three steps: first we employ a successive convex approximation technique to reduce the complexity and make the problem more tractable. Second, for any given resource block user assignment, we adopt KarushKuhnTucker (KKT) conditions to calculate the transmit power over different beams and RSMA power allocation of users over each beam. Third, using the allocated power, we design an efficient algorithm based on the greedy approach for resource block user assignment. For comparison, we propose two suboptimal schemes with fixed power allocation over different beams and random resource block user assignment as the benchmark. Numerical results provided in this work are obtained based on the Monte Carlo simulations, which demonstrate the benefits of the proposed optimization scheme compared to the benchmark schemes.

Data formats and standards for opportunistic rainfall sensors

Opportunistic sensors are increasingly used for rainfall measurement. However, their raw data are collected by a variety of systems that are often not primarily intended for rainfall monitoring, resulting in a plethora of different data formats and a lack of common standards. This hinders the sharing of opportunistic sensing (OS) data, their automated processing, and, at the end, their practical usage and integration into standard observation systems. This paper summarises the experiences of the more than 100 members of the OpenSense Cost Action involved in the OS of rainfall. We review the current practice of collecting and storing precipitation OS data and corresponding metadata, and propose new common guidelines describing the requirements on data and metadata collection, harmonising naming conventions, and defining human-readable and machine readable file formats for data and metadata storage. We focus on three sensors identified by the OpenSense community as prominent representatives of the OS of precipitation: Commercial microwave links (CML): fixed point-to-point radio links mainly used as backhauling connections in telecommunication networks Satellite microwave links (SML): radio links between geostationary Earth orbit (GEO) satellites and ground user terminals. Personal weather stations (PWS): non-professional meteorological sensors owned by citizens. The conventions presented in this paper are primarily designed for storing, handling, and sharing historical time series and do not consider specific requirements for using OS data in real time for operational purposes. The conventions are already now accepted by the ever growing OpenSense community and represent an important step towards automated processing of OS raw data and community development of joint OS software packages.

Reliability Analysis Based on Air Quality Characteristics in East Asia Using Primary Data from the Test Operation of Geostationary Environment Monitoring Spectrometer (GEMS)

Air pollutants adversely affect human health, and thus a global improvement in air quality is urgent. A Geostationary Environment Monitoring Spectrometer (GEMS) was mounted on the geostationary Chollian 2B satellite in 2020 to observe the spatial distribution of air pollution, and sequential observations have been released since July 2022. The reliability of GEMS must be analyzed because it is the first payload on the geostationary Earth orbit satellite to observe trace gases. This study analyzed the initial results of GEMS observations such as the aerosol optical depth and vertical column densities (VCD) of ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO), and compared them with previous studies. The correlation coefficient of O3 ranged from 0.90 (Ozone Monitoring Instrument, OMI) to 0.97 (TROPOspheric Monitoring Instrument, TROPOMI), whereas that of NO2 ranged from 0.47 (winter, OMI and OMPS) to 0.83 (summer, TROPOMI). GEMS yielded a higher VCD of NO2 than that of OMI and TROPOMI. Based on the sources of O3 and NO2, GEMS observed the maximum VCD at a different time (3–4 h) to that of the ground observations. Overall, GEMS can make observations several times a day and is a potential tool for atmospheric environmental analysis.

MLP-based user-applicable method for SBAS GIVD calibration: A comparative study based on CODE final GIM products

Satellite-Based Augmentation Systems (SBASs) are designed to enhance the performance of Global Navigation Satellite Systems (GNSSs) for civil aviation users. As SBAS Geostationary Earth Orbit (GEO) satellite signals are received in a wide area, far more non-aeronautical GNSS users utilize SBAS to improve navigation performance. Since ionospheric delay is the principal error source of GNSS and a leading correction aspect of SBAS, the GEO-broadcast ionospheric data quality of six SBASs over the past three years is assessed in this article. Results show that European Geostationary Navigation Overlay Service (EGNOS), System for Differential Correction and Monitoring (SDCM), and Wide-Area Augmentation System (WAAS) have the highest Grid Ionospheric Vertical Delay (GIVD) accuracy judged by the residual Standard Deviation (STD), then followed by BeiDou SBAS (BDSBAS) and Multi-functional Satellite Augmentation System (MSAS), while GPS-Aided GEO Augmented Navigation (GAGAN) is the worst. The 6 m Grid Ionospheric Vertical Error (GIVE) availability is over 90 percent of the time for most Ionospheric Grid Points (IGPs) of all tested SBASs. However, GAGAN and WAAS have a significant availability decline at 3 m GIVE. In addition, the integrity limits of MSAS and WAAS are fairly conservative. In contrast, the confidence bounds of BDSBAS and SDCM are excessively radical that fail to meet the integrity requirement. To improve the ionospheric data quality received from SBAS, a Multi-Layer Perceptron (MLP)-based user-applicable GIVD calibration method is proposed in the article. A well-trained MLP learned temporal and spatial correlations of the IGP delays and extracted transfer functions between broadcast and reference GIVDs to eliminate error. The SBAS processing errors in Differential Code Bias (DCB) compensation, GIVD estimation modeling, and GEO message quantization are rectified by the MLP trained by abundant historical data with Center for Orbit Determination in Europe (CODE) final Global Ionospheric Maps (GIMs) as reference. Test results on real-time data show that over 85 percent IGPs have STD decline after calibration. The STD declination rates of six SBASs except for SDCM are over 15 percent, and the Mean Absolute Error (MAE) and Root Mean Square Error (RMS) calibration effects are dramatic for all systems. Finally, the average GIVEs are reduced by more than 50 percent for EGNOS, GAGAN, MSAS, and WAAS with a 99.9 percent integrity level maintained. Despite no promotion on availability for BDSBAS and SDCM, the proposed method compensates for the integrity issues of the systems.

Interference Analysis of NGSO Constellation to GEO Satellite Communication System Based on Spatio–Temporal Slices

The co-frequency interference (CFI) of the non-geostationary orbit (NGSO) constellation to the geostationary earth orbit (GEO) satellite internet of things (IoT) system is an nonnegligible problem. In this paper, based on the calculation method of the NGSO constellation satellite distribution state period, we propose a global characteristic method to analyze the CFI of the NGSO constellation to the GEO satellite IoT system by spatio-temporal slices. In order to analyze and evaluate the global characteristic and overall situation of interference, the temporal and spatial cut set of interference is established by fragmenting time and gridding space. The correctness of the proposed NGSO constellation satellite distribution state period is verified by taking the OneWeb constellation’s interference to the SINOSAT-5 satellite communication system as the simulation scenario. Furthermore, the global interference characteristic of the OneWeb constellation to the SINOSAT-5 satellite communication system is analyzed with the method mentioned above in the range of 80∘ 140∘E and 0∘ 50∘N. The results show that the analysis method can reflect the overall situation of the CFI of the NGSO constellation to the GEO satellite IoT system.

An improved satellite-induced code bias correction model for BDS un-GEO satellites in consideration of elevation and azimuth angles

The satellite-induced code bias (SICB) resulting in code-phase divergences of nearly 1.0 m has been observed in the code measurements of BeiDou navigation satellite system (BDS). Since the SICB is proved to be elevation- and frequency-dependent, several SICB correction models have been proposed to remove the systematic bias, but most of them only consider elevation angles, overlooking the influence of azimuth angles, which would limit the accuracy of the correction models, especially for Medium Earth Orbit (MEO) satellites. To deal with this problem, we proposed an improved SICB piecewise correction model as a function of elevation and azimuth angles and estimated parameters for each BDS un-GEO (Geostationary Earth Orbit) satellite and each available frequency with node-separation of 1°. The epoch-difference method is employed to remove the effect of stable terms, such as phase-ambiguities, receiver- and satellite-dependent hardware delays. Moreover, to reduce the effect of code noise and multipath at low-elevation conditions, the threshold of elevation angle for the improved model is determined based on the statistics of Multipath (MP) combinations. Besides, weight-average algorithm is used to obtain the optimal MP deviations and improve the accuracy of proposed correction model in consideration of signal-to-noise (SNR). The experiment results with real GNSS data show that the SICB models are more suitable for BDS-2 MEO satellites than Inclined Geosynchronous Orbit (IGSO) satellites. The code measurements on B1 signal are more susceptible to the SICB than that on B3 signal. After applying the improved SICB correction models, the RMS errors of MP series are significantly reduced for BDS-2 un-GEO satellites. However, for BDS-3 satellites, only centimeter-level SICB deviations can be detected for all frequency-bands, and the RMS of MP variations have slight changes after applying the SICB corrections, indicating that the systematic bias in MP combinations is not obvious, especially for BDS-3 MEO satellites.

Estimating inter-satellite link Ka-band antenna phase center offsets to improve BDS-3 satellite orbit determination

Satellite antenna phase center offset (PCO) correction is essential not noly for L-band ground-tracking GNSS high-precision data processing, but also for Ka-band inter-satellite link (ISL) observations. The Ka-band ISL and L-band satellite-ground observations of 90 days from 25 November 2020 to 23 February 2021 are used for the Ka-band PCO estimation and precise orbit determination (POD) validation for BDS-3 satellites. The results show that the standard deviations of the estimated Ka-band PCOs for 29 BDS-3 satellites are 1.73, 2.63 and 3.58 cm in the X, Y and Z components, respectively. The accuracy of the Ka-band PCO estimates for medium Earth orbit satellites (MEO) is better than those of inclined geosynchronous orbit (IGSO) and geostationary Earth orbit (GEO) satellites due to a better observation geometry. The POD validation results indicate that using the estimated Ka-band PCOs can improve the ISL-based orbit determination performance. Using Ka-band ISL and L-band satellite-ground observations with 40 global stations for combined POD, the orbit overlap comparison shows that the average three-dimensional (3D) root mean square (RMS) error for 29 BDS-3 satellites is decreased from 12.6 to 6.6 cm with a reduction of 47.6%, and satellite laser ranging (SLR) validation for 4 BDS-3 satellites shows an accuracy improvement from 6 to 5 cm in RMS. When using ISL and only 7 regional ground stations are used, the average 3D RMS of orbit overlap errors is decreased from 15.9 to 10.9 cm with a reduction of 31.6%, and the RMS of SLR residuals for 4 BDS-3 satellites is decreased from 6.7 to 5.6 cm. For ISL-only POD, the average 3D RMS of orbit overlap errors is decreased from 18.0 to 12.4 cm with a reduction of 31.1%, and the RMS of SLR residuals for 4 BDS-3 satellites is decreased from 7.1 to 6.9 cm.

Sparse Bandit Learning Based Location Management for Space-Ground Integrated Networks

The Space-Ground Integrated Network (SGIN) concept constitutes a promising solution for providing seamless global coverage. However, the mobility of satellites and wireless terminals imposes unprecedented challenges on the location management in SGIN. We tackle this challenge by conceiving a split identifier (ID) and Network Address (NA) based design for providing natural mobility support, and characterize the ID-NA mapping allocation problem by exploiting the storage capacity of both Geostationary Earth Orbit Satellites (GEOSs) and Low Earth Orbiting Satellites (LEOSs) to form a spatially distributed binding resolution system and optimize the caching reward in each LEOS. By considering the large quantity of ID-NA mapping and the sparsity of popular mapping having positive mean caching rewards, we formulate the mapping allocation problem as a sparse Multi-Armed Bandit (MAB) learning procedure, where the mappings are treated as the arms and the LEOSs act as the players. A distributed learning algorithm, namely the Sparse Upper confidence bound based Learning aided Caching algorithm (SULC), is proposed for estimating the mean caching rewards of mappings and selecting the optimal mappings for caching. Moreover, we derive a sub-linear upper bound of the cumulative learning regret to prove the learning efficiency of the proposed SULC. Extensive simulations have been conducted to show that the proposed SULC can quickly identify the popular mappings and provide near-optimal content hit rates. In contrast with the existing solutions, SULC has higher caching rewards and can significantly reduce the cumulative regret after a short period of learning.

Real-Time Precise Position Estimation of Geostationary Earth Orbit Satellites Using Ground Beacons

This paper presents a method for precise estimation of the position of Geostationary Earth Orbit (GEO) satellite, using radio-waves, from at least four beacons mounted on the ground. The locations of these beacons are known and fixed with respect to an observer on the Earth. GPS-based instantaneous position determination has been studied in the literature extensively since early 1980’s, and has been used on-board Low-Earth satellites. However, for Geostationary Earth Orbits (GEO) the visibility of Global Positioning System (GPS) satellites is limited to a small conical annulus formed by the main beam of the GPS satellite on the far side of the GPS-Earth cone. So at any measurement epoch there may not be four GPS satellites available to form four independent equations to solve explicitly for the required four unknowns. GEO being the most prominent of orbits with diverse applications, so we propose in this paper a new concept of use of ground based beacons for real time precise orbit determination of GEO satellites. The technique presented in this paper is inverse Global Navigation by Satellite Systems (GNSS). The usual case is GNSS/GPS signal from space is used to estimate the position of the satellite/object fitted with GNSS receiver. In the present scheme GEO satellite is fitted with a receiver and beacons are mounted at the ground in India or globally. The present scenario is thus different but slightly. This interesting concept will be useful for position estimation of GEO satellites equipped with a receiver to get measurements or observables from beacons. The simulation results have shown that it is possible to find the precise position of the Earth orbit satellites at GEO altitude.

High Reliable Uplink Transmission Methods in GEO–LEO Heterogeneous Satellite Network

As a significant component of non-terrestrial networks, satellite communication has gradually evolved into a heterogeneous topology where the network nodes are classified as low Earth orbit (LEO) and geostationary Earth orbit (GEO) nodes. Considering the advantage of low transmission delay of LEO satellites in a heterogeneous network, ground users are arranged to access LEO satellites in the first priority. By fully understanding the equivalent channel gain difference in the beam-edge and beam-center users, we develop non-orthogonal multiple access (NOMA) in an LEO network where different users are allocated in the same resource block. As a complementary strategy, the beam-edge user has the ability to connect the GEO satellite if the LEO links are not available. That is, the two users are served cooperatively by LEO and GEO satellites in an orthogonal manner. In this paper, we provide deep insights for the uplink transmission performance of NOMA and cooperative orthogonal multiple access methods. As a general metric, the analytical expressions of outage probability are derived and the diversity orders are also provided. The simulation results show that NOMA is capable of providing remarkable performance in low signal-to-noise ratio regions and is more promising when the channels are assumed to be ordered.

Energy-Efficient and QoS-Aware Computation Offloading in GEO/LEO Hybrid Satellite Networks

Benefiting from advanced satellite payload technologies, edge computing servers can be deployed on satellites to achieve orbital computing and reduce the mission processing delay. However, geostationary Earth orbit (GEO) satellites are hindered by long-distance communication, whereas low Earth orbit (LEO) satellites are restricted by time windows. Relying solely on GEO or LEO satellites cannot meet the strict quality of service (QoS) requirements of on-board missions while conserving energy consumption. In this paper, we propose a computation offloading strategy for GEO/LEO hybrid satellite networks that minimizes total energy consumption while guaranteeing the QoS requirements of multiple missions. We first innovatively transform the on-board partial computation offloading problem, which is a mixed-integer nonlinear programming (MINLP) problem, into a minimum cost maximum flow (MCMF) problem. Then, the successive shortest path-based computation offloading (SSPCO) method is introduced to obtain the offloading decision in polynomial time. To evaluate the effectiveness and performance of SSPCO, we conduct a series of numerical experiments and compare SSPCO with other offloading methods. The experimental results demonstrate that our proposed SSPCO outperforms the reference methods in terms of total energy consumption, QoS violation degree, and algorithm running time.