Earth Orbit Satellite Research Articles

Improved artificial bee colony algorithm-based channel allocation scheme in low earth orbit satellite downlinks

In low earth orbit (LEO) constellations, channel utilization is low owing to variations in the traffic distributions between beams. LEO satellites improve channel utilization via the full-band multiplexing technology. However, such satellites produce significant inter-beam interference. Additionally, this inter-beam interference becomes more aggravated owing to the requirements of multiple satellite coverage. To resolve this issue, we propose a LEO channel allocation scheme based on an improved artificial bee colony (IABC) algorithm. This scheme considers the difference in inter-beam communication traffic and the limitation of co-channel interference. A binary integer-programming model and IABC algorithm allocate channels to maximize the system throughput. The channel allocation matrix corresponds to a feasible solution in the IABC algorithm. The simulation results verify the excellent performance of the proposed scheme in terms of the throughput, blocking rate, and propagation delay compared with the performance of traditional schemes.

An evaluation of GNSS radio occultation atmospheric profiles from Sentinel-6

The Global Navigation Satellite System (GNSS) radio occultation (RO) significantly impacts climate change monitoring. GNSS RO is based mainly on the refraction of the GNSS signals transmitted by satellites and received by a receiver on a Low Earth Orbit (LEO) satellite. Sentinel-6 (S6) is the first satellite from the Sentinel missions to retrieve atmospheric parameters using the RO technique. Temperature, pressure, and water vapor profiles can be retrieved using S6 based on the refraction of GNSS signals. This research evaluated the distribution and coverage of GNSS RO data from S6. This research also aims to evaluate the results of GNSS RO products, especially temperature from S6, from January 2022 to June 2022. The results of S6 are compared with the results from the Meteorological Operational Polar Satellite series (MetOp-B and MetOp-C) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) dataset. Our results indicate that S6 allows for many RO observations in space by receiving signals from the Global Positioning System (GPS) and Russia's Global Navigation Satellite System (GLONASS). S6 provides monthly RO profiles from GPS that are greater than monthly RO profiles from GLONASS. Results show that S6 provides more GNSS RO data than MetOp-B and MetOp-C. The findings indicate that the distribution of GNSS RO events from S6 over the globe is uniform in longitude and non-uniform at latitude, with the minimum number at the poles. This paper makes a significant contribution to exploring the atmosphere with the S6 as a promising satellite for weather forecasting and monitoring climate change.

An Improved Doppler-Aided Smoothing Code Algorithm for BeiDou-2/BeiDou-3 un-Geostationary Earth Orbit Satellites in Consideration of Satellite Code Bias

The extensive use of carrier-aided smoothing code (CSC) filters has led to a reduction in the noise level of raw code measurements in GNSS positioning and navigation applications. However, the existing CSC technique is sensitive to the changes in the integer ambiguity, and then the smoothing procedure needs to be restarted in the presence of cycle slips. As the Doppler shift is instantaneously observed and immune to cycle slips, the Doppler-aided smoothing code (DSC) algorithm would be more promising in a challenged environment. Based on the Hatch filter, an optimal DSC approach is proposed with the principle of minimum variance. Meanwhile, to inhibit the effect of the integral cumulative error of the Doppler, a balance factor is adopted to adjust the contributions of raw code and DSC. The noise level of code observable is not only affected by thermal noise, but also limited by systematic bias. Satellite code bias (SCB) was identified in the raw code observable on each frequency for each BDS-2 satellite. By minimizing the sum of the absolute value of residuals, the polynomial segment fitting algorithm as a function of elevation angles is applied to establish the SCB correction model based on epoch-differenced multipath (MP) deviations. Finally, different types of experiments demonstrate the validity and efficiency of the refined DSC filter with SCB corrections on each available frequency for BDS un-GEO satellites.

Millimeter accuracy SLR bias determination using independent multi-LEO DORIS and GPS-based precise orbits

Satellite Laser Ranging (SLR) has become an invaluable core technique in numerous geodetic applications. SLR measurements to passive spherical satellites essentially contribute to the determination of geocenter coordinates and global scale in the International Terrestrial Reference Frame (ITRF) realizations. In addition, SLR measurements to active satellites in Low Earth Orbit (LEO) are up to now mostly used for an independent validation of orbit solutions, usually derived by microwave tracking techniques based on Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) or Global Navigation Satellite Systems (GNSS). This allows for the analysis of systematic orbit errors (e.g., originating from poorly known non-gravitational perturbations or sensor offsets) not only in the radial direction (key to satellite altimetry missions), but in three dimensions.Major obstacles to reach the millimeter accuracy and stability goals of 0.1mm/y (at decadal time scales) of the Global Geodetic Observing System (GGOS) are station-satellite measurement biases and on-ground/board coordinate offsets. Among the observatories of the International Laser Ranging Service (ILRS) a large diversity of measurement qualities exists, and the calibration of station-dependent errors is now necessary to further exploit SLR data for present and future climate-driven needs.We demonstrate that the analysis of SLR data to active LEO satellites equipped with DORIS or GNSS receivers is a promising means to characterize SLR biases and their stability. Using two independent selections of Earth observation missions in LEOs (consisting of six altimetry, three magnetic field and two gravity field satellites) with three different analysis software packages (Bernese, ZOOM, Napeos), we estimate SLR range biases for all involved tracking stations on a yearly basis. We find that for many of the stations independently estimated sets of biases agree on a few-mm level and that the inclusion of satellites from multiple missions allows rendering the bias estimation more robust and in particular less prone to geographically correlated orbit errors. This shows that microwave-derived orbits of active LEO satellites, nowadays of very high quality due to numerous advances in modeling and analysis techniques, can serve as interesting sources for SLR station calibration in demanding climate applications.

Evaluation of delay tolerant network routing protocols for data streaming through LEO constellation

In the Era of Mega Low Earth Orbit (LEO) satellite constellation, the efficient networking through Inter-Satellite Links (ISLs) plays a vital role in its mission success. The deployed networking resources must be justified regarding the feasibility, reliability, and Quality of Service (QoS). The main challenge of such networks is the ISLs intermittence due to the dynamic nature of the constellation topology. In addition to the space environment. From this perspective, Delay Tolerant Network (DTN) protocols were proposed for alleviating the events of intermittence. This paper introduces a technique for using the discrete-event network simulator (NS3) for the simulation of LEO constellation networks. This technique considers the dynamic nature of network’s nodes in data streaming through ISLs. The paper presents a performance assessment of LEO constellation networks dedicated for forwarding the payload data through ISLs. The performance measures include both the delay and delivery ratio. The assessment considers different local resources such as transmitted power, Queue size, and transmission rate. The performance measures were applied for some selected DTN protocols such as “Epidemic” and “Spray and Wait”. The results illustrate the effects of different network resources and configurations that may affect the constellation mission.

Hybrid Multibeamforming Receiver With High-Precision Beam Steering for Low Earth Orbit Satellite Communication

A hybrid multibeamforming receiver for low Earth orbit (LEO) satellite communication in the Ku-band is designed and tested. The proposed receiver is implemented with eight channels to enable multibeam control. The proposed receiver, including both analog and digital beamforming structures, is capable of multibeam reception using both analog and digital beamforming techniques simultaneously or selectively. Analog beamforming is implemented by employing a local oscillator phase shifter using direct digital synthesis and phase-locked loop (PLL) structures. In digital beamforming, a software-defined radio can control the phase of the signal in the digital baseband. The multibeam received using the proposed hybrid multibeamforming receiver was measured at 11.7 GHz and 12.7 GHz in an anechoic chamber. The phase-control resolutions of analog and digital beamforming were 0.022° and 0.72°, respectively. Analog beam-switching speed is slower than digital beamforming because it depends on the settling time of the PLL circuit, but it has a high phase-control resolution. Therefore, by using analog and digital beamforming when precise beam tilting and fast beam switching are required, respectively, the proposed hybrid multibeamforming is shown to be suitable in accordance with the communication situation.

Beamforming for LEO satellite communication based on FDA

AbstractDue to the time‐varying phase in frequency diverse arrays (FDAs), traditional phase‐based secure communication (SC) methods cannot be utilized. In this reported work, the automatic scanning property of FDAs (time‐varying property) was rederived. This property allows for the presetting of the beam scanning time towards the desired receiver (Bob). Subsequently, this time‐carrying beam design was applied to Low Earth Orbit (LEO) satellites. A satellite‐to‐ground communication method is proposed based on time intervals, which effectively prevents the interception of information by an undesired receiver (Eve). Simulation results are presented to validate the effectiveness of the proposed method.

Daily Plasmaspheric TEC Variations From COSMIC GPS Observations Based on RBF Neural Network‐Kriging Method

AbstractThe low Earth orbit (LEO) satellite provides valuable direct observations for scientific investigation of the plasmasphere, while the plasmaspheric total electron content (PTEC) with a high temporal resolution cannot be precisely estimated due to fewer LEO satellites. In this paper, a novel joint method of radial basis function neural network—Kriging (RBF‐Kr) method is designed to construct the daily PTEC model using the Constellation Observing System for Meteorology, Ionosphere and Climate Global Positioning System observations during the low (2009) and high (2013) solar activity years. Compared with the original RBF method, the RBF‐Kr method reduces the mean absolute error and root mean square error from 0.77 to 0.60 TEC unit (TECU) and 0.99 to 0.80 TECU, respectively. The correlation coefficient (Corr) increased from 0.90 to 0.94. Furthermore, daily PTEC variations show that the PTEC at low latitudes is evenly distributed during equinox periods. The South American‐Atlantic Ocean sector has a peak and trough in PTEC during the December and June solstices. A certain symmetrical distribution of PTEC is observed in the latitudinal direction, and the symcenter moves toward the summer hemisphere. The duration of extremal PTEC at 60°W is observed, which lasted up to more than 80 days around the December solstice. An obvious correlation between the solar flux and PTEC is found with up to 0.86, indicating that daily PTEC variations are mainly related to solar activities.

Olive Branch Learning: A Topology-Aware Federated Learning Framework for Space-Air-Ground Integrated Network

The space-air-ground integrated network (SAGIN), one of the key technologies for next-generation mobile communication systems, can facilitate data transmission for users all over the world, especially in some remote areas where vast amounts of informative data are collected by Internet of remote things (IoRT) devices to support various data-driven artificial intelligence (AI) services. However, training AI models centrally with the assistance of SAGIN faces the challenges of highly constrained network topology, inefficient data transmission, and privacy issues. To tackle these challenges, we first propose a novel topology-aware federated learning framework for the SAGIN, namely Olive Branch Learning (OBL). Specifically, the IoRT devices in the ground layer leverage their private data to perform model training locally, while the air nodes in the air layer and the ring-structured low earth orbit (LEO) satellite constellation in the space layer are in charge of model aggregation (synchronization) at different scales. To further enhance communication efficiency and inference performance of OBL, an efficient Communication and Non-IID-aware Air node-Satellite Assignment (CNASA) algorithm is designed by taking the data class distribution of the air nodes as well as their geographic locations into account. Furthermore, we extend our OBL framework and CNASA algorithm to adapt to more complex multi-orbit satellite networks. We analyze the convergence of our OBL framework and conclude that the CNASA algorithm contributes to the fast convergence of the global model. Extensive experiments based on realistic datasets corroborate the superior performance of our algorithm over the benchmark policies.

A Survey on IoT Positioning Leveraging LPWAN, GNSS, and LEO-PNT

Location data is an important piece of information in many Internet of Things (IoT) applications. Global Navigation Satellite Systems (GNSS) have been established as the standard for large-scale localization. However, the rapidly increasing need to locate IoT devices in recent years has exposed several shortcomings of traditional GNSS approaches. These limitations include the weak signal propagation in indoor and dense environments, the inability to calculate or obtain a location remotely, and a high energy consumption. Therefore, several industries have shown an increasing demand for alternative and innovative positioning solutions that are more suited in an IoT context. Hence, we conduct a survey on state-of-the-art, large-scale and energy-efficient positioning techniques for IoT applications. More specifically, we analyze the performance of terrestrial-based Low Power Wide Area Network (LPWAN) techniques, novel GNSS solutions, and innovative positioning techniques leveraging Low Earth Orbit (LEO) satellite constellations. A comparison is made in terms of 16 dimensions including energy consumption, positioning accuracy, coverage, and scalability. The analysis shows that interoperability between technologies is key to enable energy-efficient communication and positioning applications in the emerging market of satellite IoT.

Analysis performance of navigation constellation satellite failure and enhancement of LEO navigation

The stable operation of navigation satellite constellation is related to national economy and national defense security. The failure of any one or two satellites has little impact on the overall performance of the global navigation satellite constellation, and the availability of the navigation constellation decreases with the increase of the number of failed satellites. First, a typical medium earth orbit Walker-δ 24/3/1 constellation configuration was designed. Second, the service performance of the navigation constellation under different failure modes was analyzed. The weaknesses of the constellation were identified in combination with the availability data of the navigation constellation. Then, the overall performance of the navigation constellation after the low earth orbit satellite constellation compensates for the failure of the medium earth orbit satellite constellation is analyzed. The simulation results show that the failure of 5 global navigation satellites will reduce the availability of navigation constellation to 71%, and the hybrid navigation constellation can recover the availability to more than 97%. The orbital altitude and inclination of low orbit satellites affect the overall performance of the hybrid navigation constellation. The research results can provide reference for the demonstration of hybrid navigation constellation scheme.

Analysis of AMS(R)S VHF Communication and Voice Communication Simulation Using Mathematical Programming Language

To expand the coverage of current aviation VHF communication services, it is necessary to develop a satellite-based VHF communication system. This research aims to analyze the satellite link budget calculations for VHF AMS(R)S frequencies using a Low Earth Orbit (LEO) satellite at an altitude of 600 km, in accordance with the studies conducted by ICAO and ITU. The link budget calculation, using parameters such as aircraft antenna gain = -1 dBi, satellite antenna gain = 8 dBi, RF power of the aircraft = 16 watts, and RF power of the satellite = 85 watts, results in satellite receiver sensitivity between -107 dBm - 25.56 dB, as well as aircraft receiver sensitivity between -93 dBm - 38.65 dB. When simulating an end-to-end link budget (loopback: aircraft-satellite-aircraft between 14.92 dB - 14 dB. Simulations were also carried out for voice communication using an AWGN channel illustration with an Eb/No of 10 dB, resulting in the performance of the VHF audio link.

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.

Analytical modelling and sizing of supercapacitors for spacecraft hybrid energy storage systems

The vast majority of Earth-orbiting satellites carry an electrical power subsystem (EPS) which main components are solar panels and secondary batteries. During eclipse periods, satellites are powered only by rechargeable batteries which have a large energy density but a limited power density. This fact limits the power capabilities of small satellites during eclipse periods. Due to the large power density of Supercapacitors (SCs), ground and on-orbit tests have been conducted to verify their applicability on satellite EPSs. At the moment, no studies are underway on the issue of sizing SCs for eclipse operations. Hybrid configuration could reduce the mass and volume of EPS or maintain those reference values but increasing peak power capabilities. This paper deals with this issue. On the one hand, novel analytical expressions of a variable capacitance SCs are derived, including time–voltage dependence in constant power applications. Also an equivalent formulation for a SCs bank (SCsB) is derived. On the other hand, a SCsB sizing procedure is presented, considering the energy and power requirements of a particular space mission as an input. Finally, a simple mission is analysed, the results showing an improvement on the hybrid EPS design with respect to the traditional, being the mass reduction of 36%.

Satellite Collision and Fragmentation Probabilities Using Radar-Based Size and Mass Estimates

Most conjunctions between Earth-orbiting satellites involve unknown objects, typically debris created by explosions or collisions. This study formulates methods to estimate probabilities of collision and fragmentation for such conjunctions, which depend on the estimated sizes and masses of the unknown objects. Analysis of radar cross-section (RCS) measurements provides estimated sizes, found to be accurate at the 90% confidence level to within a factor of 0.59 for potential underestimations and to within a factor of 3.1 for potential overestimations. For satellites that experience measurable atmospheric drag orbital perturbations, combining RCS data with orbit determination ballistic coefficients provides mass estimates accurate to within factors of 0.47 to 10.9 at the 90% confidence level. For satellites with perigee altitudes above 450 km, combining RCS data with solar radiation pressure coefficients provides mass estimates accurate to within factors of 0.44 to 5.6 at 90% confidence. The collision and fragmentation risk assessment formulation accounts for these size and mass estimation uncertainties. Specifically, conjunction collision probabilities formulated as statistically expected values account for the RCS-based size estimation uncertainties. Fragmentation probabilities, which measure the likelihood of producing more than a threshold number of collision fragments, account for both size and mass estimation uncertainties.

StarUnLink: identifying and mitigating signals from communication satellites in stellar spectral surveys

ABSTRACT A relatively new concern for the forthcoming massive spectroscopic sky surveys is the impact of contamination from low earth orbit satellites. Several hundred thousand of these satellites are licensed for launch in the next few years and it has been estimated that, in some cases, up to a few per cent of spectra could be contaminated when using wide field, multifibre spectrographs. In this paper, a multistaged approach is used to assess the practicality and limitations of identifying and minimizing the impact of satellite contamination in a WEAVE-like stellar spectral survey. We develop a series of convolutional-network-based architectures to attempt identification, stellar parameter and chemical abundances recovery, and source separation of stellar spectra that we artificially contaminate with satellite (i.e. solar-like) spectra. Our results show that we are able to flag 67 per cent of all contaminated sources at a precision level of 80 per cent for low-resolution spectra and 96 per cent for high-resolution spectra. Additionally, we are able to remove the contamination from the spectra and recover the clean spectra with a <1 per cent reconstruction error. The errors in stellar parameter predictions reduce by up to a factor of 2–3 when either including contamination as an augmentation to a training set or by removing the contamination from the spectra, with overall better performance in the former case. The presented methods illustrate several machine learning mitigation strategies that can be implemented to improve stellar parameters for contaminated spectra in the WEAVE stellar spectroscopic survey and others like it.

Space debris remediation using space-based lasers

Centimetre and sub-centimetre debris fragments present a significant threat to many operational satellites in Earth orbit. When debris can be tracked, the preferred approach is collision avoidance to slightly alter the orbit of the at-risk satellite, resulting in an along-track displacement which compounds over several orbits. Although numerous strategies for active debris removal and remediation have been proposed, most such methods involve rendezvous maneuvers with targeted pieces of debris prior to some mechanical interaction. While such approaches are appropriate for removing larger objects which are potential sources of further debris, they are unsuitable for application to fragments which are too small to be accurately tracked from Earth and with which a rendezvous would be challenging.This paper investigates the use of photon pressure and ablation from space-based lasers to directly affect the orbits of small debris fragments, both to lower their orbits and lifetimes, and to reduce collision risk with operational satellites. A mission concept is studied which enables the cataloguing of debris shells of small fragments produced after breakup events, while also allowing the encountered fragments to be illuminated by a laser on board the observation satellite(s). The concept takes advantage of a laser’s ability to impart momentum at a distance by employing opportunistic interaction with passing fragments, assuming no prior knowledge of their orbits and no ability to rendezvous. The impact of the mission over a 10-year operational lifetime is simulated statistically by analysing the dynamics of typical encounters and the achievable impact on fragment orbits. The effects of off-beam-axis components of the applied ΔV and its implications for beam tracking are also investigated, along with the effects of extreme laser fluence on fragment attitude.

GNSS-based precise orbit determination for maneuvering LEO satellites

Maneuverability is essential for low Earth orbit (LEO) satellites to fulfill various operational objectives. However, the precise orbit determination (POD) process might deteriorate due to imperfect satellite orbital dynamics modeling. This article develops a generic POD strategy with maneuver handling for LEO satellites equipped with high-performance spaceborne Global Navigation Satellite System (GNSS) receivers. Given the time span of an executed maneuver, a set of constant thrust accelerations in the satellite body-fixed reference frame is estimated without using a-priori maneuver accelerations. In addition, different numbers of velocity pulses are estimated at predefined epochs determined by the duration of a maneuver. POD experiments are done for the GRACE-FO and Sentinel-3 satellites, for which the orbit maneuvers vary significantly. The orbits are assessed via internal consistency checks and external orbit validations. Internally, in each direction, the agreement between the reduced-dynamic and kinematic orbits reaches a level of 1 cm, which is comparable with the reference day without maneuvers. Externally, comparisons with the official GRACE-FO products and orbits from the Sentinel-3 Copernicus POD Quality Working Group confirm the reliability of the new orbits with maneuver handling. Finally, satellite laser ranging and K-band ranging measurements indicate a 1-cm accuracy of the absolute orbits and a 2-mm accuracy of the GRACE-FO relative orbits. The maneuver handling strategy is tested in the Bernese GNSS Software, consistently developed at the Astronomical Institute of the University of Bern.

Thermospheric density predictions during quiet time and geomagnetic storm using a deep evidential model-based framework

Knowledge of the thermospheric density is essential for calculating the drag in low Earth orbit satellites. Existing models struggle to predict density accurately. In this paper, we propose thermospheric density prediction using a deep evidential model-based framework that incorporates empirical models, accelerometer-inferred density from the CHAMP satellite, and geomagnetic and solar indices. The framework is investigated on both quiet and storm conditions. Our results demonstrate that the proposed model can predict the thermospheric density with high accuracy and reliable uncertainty in both quiet and storm times. The predicted results from the evidential model are advantageous over the Gaussian Processes (GPs) model in our previous studies. Furthermore, the proposed model can also provide insightful aleatoric and epistemic uncertainties.

Measuring and monitoring light pollution: Current approaches and challenges

Understanding the causes and potential mitigations of light pollution requires measuring and monitoring artificial light at night (ALAN). We review how ALAN is measured, both from the ground and through remote sensing by satellites in Earth orbit. A variety of techniques are described, including single-channel photometers, all-sky cameras, and drones. Spectroscopic differences between light sources can be used to determine which are most responsible for light pollution, but they complicate the interpretation of photometric data. The variability of Earth’s atmosphere leads to difficulty in comparisons between datasets. Theoretical models provide complementary information to calibrate experiments and interpret their results. Here, we identify several shortcomings and challenges in current approaches to measuring light pollution and suggest ways forward.