Satellite Research Articles

Deep learning for quality control of surface physiographic fields using satellite Earth observations

Abstract. A purposely built deep learning algorithm for the Verification of Earth System ParametERization (VESPER) is used to assess recent upgrades to the global physiographic datasets underpinning the quality of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF), which is used in both numerical weather prediction and climate reanalyses. A neural network regression model is trained to learn the mapping between the surface physiographic dataset, plus the main meteorologic fields from ERA5, and the MODIS satellite skin temperature observations. Once trained, this tool is applied to rapidly assess the quality of upgrades to the physiographic fields used by land surface schemes. Upgrades which improve the prediction accuracy of the machine learning tool indicate a reduction in the errors in the surface fields used as input to the surface parameterization schemes. Conversely, incorrect specifications of the surface fields decrease the accuracy with which VESPER can make predictions. We apply VESPER to assess the accuracy of recent upgrades to the permanent lake and glacier covers, as well as of planned upgrades to represent seasonally varying water bodies (i.e. ephemeral lakes). We show that, for grid cells where the lake fields have been updated, the prediction accuracy of VESPER in the land surface temperature (as quantified by the mean absolute error) improves by 0.37 K on average, whilst for the subset of points where the lakes have been completely removed and replaced with bare ground, the improvement is 0.83 K. We also show that updates to the glacier cover improve the prediction accuracy by 0.22 K. We highlight how neural networks such as VESPER can assist the research and development of surface parameterizations and their input physiography to better represent Earth’s surface coupled processes in weather and climate models.

Simulation for the test mass charging rate in the Tianqin orbit

For the purpose of detecting gravitational waves from space, high-energy particles will infiltrate the satellite’s structure and accumulate charges on the test mass, consequently diminishing detection performance. Present investigations into the charging rate of the test mass typically rely on the particle distribution of Earth orbit. However, the influence of the Earth’s magnetosphere needs to be considered for the Tianqin detector because of its geocentric orbit. In this paper, artificial neural network is used to fuse satellite data and the galactic cosmic rays model to give the distribution of high-energy particles in the Tianqin orbit. And then, the charging rate is estimated by Monte Carlo simulation. The simulation results show that the flux of hundreds of MeV particles is a little higher than that in Earth orbit, which lead to 3−4 e s−1 higher than LISA, i.e. the charging rate of approximately 43 e s−1 during periods of solar minimum and 19 e s−1 during periods of solar maximum. These findings hold substantial implications for guiding the design of the charge management system.

Optical and structural designs for GEO orbit remote-sensing satellite and its camera system

Since 1957, when the Soviet Union launched the first artificial satellite, Sputnik I, attempts have been made to bring convenience to people by interacting with terrestrial facilities through orbital space. Geostationary Earth-orbiting remote sensing satellites provide the ability to continuously scan and explore a specific area, allowing researchers to obtain more accurate information about the Earth, which benefits mankind in many ways. This paper analyzes the payload satellite camera carried by remote sensing satellites, explains the working principle of the camera, and outlines the relevant parameters and their concepts. Taking China's Gaofen-4 as an example, it analyzes the design and limitations of the common satellite camera used in this template from the perspectives of thermodynamic, mechanical, and optical environments. Meanwhile, the article gives an outlook on the future development trend of Geostationary Earth orbit remote sensing satellites.

High-efficiency radiation attenuation shields of polymer composites for the low earth orbit space environment – multilayer shielding simulation system-based investigations

The polymer/metal hybrids have been used as a solution for the mitigation of ionizing radiation in space for sensitive electronics components, particularly for a proton-rich Low Earth Orbit (LEO) environment. Consequently, radiation attenuation analysis of polymer/metal hybrid composites has been investigated. Radiation attenuation analysis has been performed using online GEANT4 (simulation toolkit) and the Multilayer Shielding Simulation System (MULASSIS) for the LEO space environment. The shielding potential of polymers, such as poly(dimethyl siloxane), poly(methyl methacrylate), polyurethane and ultra-high molecular weight polyethylene, were analyzed with optimized compositions. It was observed that the pristine PDMS attenuated relatively more radiations than other polymer matrices. For modelling of hybrid radiation material composition, PDMS and carbon fibre fabric-derived composite laminates along with metal sheets (Aluminum Al, Tantalum Ta or Tungsten W) were used to analyze hybrid compositions. Here, hybrid composition performance was analyzed as a function of various areal densities. Analyzed polymer laminate/metal hybrid compositions performed better to attenuate LEO radiations up to 42.29%, compared to conventional Al (areal densities of 0.2–1.0 g/cm2). The maximum magnitude of attenuation was found at an areal density of 1.0 g/cm2 for Ta and W metal composition (39.44% and 42.29%, respectively), and so performed better than Al metal. Improved attenuation ratios of the hybrid compositions revealed that the hybrid laminate/metal shields can replace conventional Al shields towards LEO space radiations.

Implementing materials fragmentation in the Life Cycle Assessment of orbital spacecraft

Space debris are a primary environmental concern for the sustainability of space mission activities. When considering terrestrial applications, the Life Cycle Assessment represents a widely standardised technique for estimating the environmental impacts of human activities; however, its implementation in the space-related value chain is still in an early stage. In this study, the implications of two alternative materials in the development of a CubeSat structural bus are investigated with reference to the well-established categories for the Life Cycle Impact Assessment. Moreover, the potential impact of these materials on the orbital environment is quantified by the evaluation of the number of generated fragments upon collision for different significant low Earth orbits. The results of this study allow to quantify the impact of alternative design solutions for space systems on the terrestrial environment as well as the degradation of the orbital resources as a result of the space debris generation.

A NavCom Signal Authentication Scheme Based on Twice Two-Way Satellite Time Transfer

Low Earth Orbit (LEO) satellite communication systems typically achieve identity authentication through the encryption and decryption of two-way information, which requires complex key management systems. In contrast, the integration of navigation and communication (NavCom) signals provides novel opportunities for physical observation and authentication solutions due to its measurement functions. This paper introduces a novel signal authentication scheme based on twice two-way satellite time transfer (TWSTT) for LEO satellite systems. It leverages the non-mutated nature of the clock difference to ascertain the legitimacy of the signal by measuring the clock difference of signals at different instances. Unlike traditional authentication methods, this approach directly exploits the temporal and spatial characteristics of the signal, negating the necessity for intricate authorization key systems. Additionally, it adeptly tackles the challenges posed by spoofing interference. The performance analysis indicates that this scheme can achieve a high detection probability for the repeater spoofing signal in the low carrier-to-noise ratio conditions.

Troposphere Sensing Using Grazing‐Angle GNSS‐R Measurement From LEO Satellites

AbstractThis paper studies a new concept of using global navigation satellite system (GNSS) signals coherently reflected over relatively smooth ocean and ice surfaces from very low elevation angles (below ∼8°) and received by low Earth orbit (LEO) satellites to retrieve the tropospheric information. This approach can provide horizontal profiles of tropospheric zenith delay and total column water vapor (TCWV) with centimeter‐level high precision and spatial resolutions of tens of km by ∼1 km, depending on the elevation angle, with a sampling spacing of ∼100 m. This approach can potentially be applied to most sea ice and calm ocean areas and provide tropospheric sensing data, which can complement and augment existing observation systems. A few case studies are conducted in this paper using the Spire grazing‐angle GNSS‐R data. The retrieved TCWV is compared to ERA5 products and the Sentinel‐3 Ocean and Land Color Instrument measurements and shows promising performances. The errors associated with the GNSS‐R tropospheric measurements are also discussed.

The multiview observatory for solar terrestrial science (MOST)

We report on a study of the Multiview Observatory for Solar Terrestrial Science (MOST) mission that will provide comprehensive imagery and time series data needed to understand the magnetic connection between the solar interior and the solar atmosphere/inner heliosphere. MOST will build upon the successes of SOHO and STEREO missions with new views of the Sun and enhanced instrument capabilities. This article is based on a study conducted at NASA Goddard Space Flight Center that determined the required instrument refinement, spacecraft accommodation, launch configuration, and flight dynamics for mission success. MOST is envisioned as the next generation great observatory positioned to obtain three-dimensional information of large-scale heliospheric structures such as coronal mass ejections, stream interaction regions, and the solar wind itself. The MOST mission consists of 2 pairs of spacecraft located in the vicinity of Sun-Earth Lagrange points L4 (MOST1, MOST3) and L5 (MOST2 and MOST4). The spacecraft stationed at L4 (MOST1) and L5 (MOST2) will each carry seven remote-sensing and three in-situ instrument suites, including a novel radio package known as the Faraday Effect Tracker of Coronal and Heliospheric structures (FETCH). MOST3 and MOST4 will carry only the FETCH instruments and are positioned at variable locations along the Earth orbit up to 20° ahead of L4 and 20° behind L5, respectively. FETCH will have polarized radio transmitters and receivers on all four spacecraft to measure the magnetic content of solar wind structures propagating from the Sun to Earth using the Faraday rotation technique. The MOST mission will be able to sample the magnetized plasma throughout the Sun-Earth connected space during the mission lifetime over a solar cycle.

Computation Offloading and Resource Allocation Based on P-DQN in LEO Satellite Edge Networks.

Traditional low earth orbit (LEO) satellite networks are typically independent of terrestrial networks, which develop relatively slowly due to the on-board capacity limitation. By integrating emerging mobile edge computing (MEC) with LEO satellite networks to form the business-oriented "end-edge-cloud" multi-level computing architecture, some computing-sensitive tasks can be offloaded by ground terminals to satellites, thereby satisfying more tasks in the network. How to make computation offloading and resource allocation decisions in LEO satellite edge networks, nevertheless, indeed poses challenges in tracking network dynamics and handling sophisticated actions. For the discrete-continuous hybrid action space and time-varying networks, this work aims to use the parameterized deep Q-network (P-DQN) for the joint computation offloading and resource allocation. First, the characteristics of time-varying channels are modeled, and then both communication and computation models under three different offloading decisions are constructed. Second, the constraints on task offloading decisions, on remaining available computing resources, and on the power control of LEO satellites as well as the cloud server are formulated, followed by the maximization problem of satisfied task number over the long run. Third, using the parameterized action Markov decision process (PAMDP) and P-DQN, the joint computing offloading, resource allocation, and power control are made in real time, to accommodate dynamics in LEO satellite edge networks and dispose of the discrete-continuous hybrid action space. Simulation results show that the proposed P-DQN method could approach the optimal control, and outperforms other reinforcement learning (RL) methods for merely either discrete or continuous action space, in terms of the long-term rate of satisfied tasks.

Re‐entry safety: Analysis and plasma wind tunnel testing of spacecraft design solutions to reduce on‐ground casualty risk

In compliance with ISO 24,113 and ESA Space Debris Mitigation requirements, spacecrafts in Low Earth Orbit (LEO) must be removed from their operational orbit within 25 years and re-enter the Earth's atmosphere having an on-ground casualty risk lower than 1 in 10,000.To maximize the number of uncontrolled re-entries, which have much less impact on system mass and costs, ESA's Clean Space initiative is investigating design for containment (D4C) techniques and collaborating with European industries and space agencies to assess, model, analyse, and test new concepts through re-entry tools and plasma wind tunnel experiments. The main objectives are to understand the survivability of materials and techniques suitable for different containment concepts, to improve re-entry modelling, and implement effective D4C measures.This paper shows the results of these activities, that have been the first milestones in the knowledge of D4C, although further investigations are needed.

Probing Physicochemical Performances of 3D Printed Carbon Fiber Composites During 8‐Month Exposure to Space Environment

AbstractCarbon fiber reinforced polymers (CFRPs) offer exceptional properties that make them highly relevant in the aerospace industry, such as high thermal conductivity and an outstanding strength‐to‐weight ratio. Advances in additive manufacturing have expanded the aerospace applications of CFRPs, even allowing for in‐space fabrication of complex structures. Understanding the stability of CFRPs in the harsh conditions of low Earth orbit (LEO) is crucial. LEO exposes materials to extreme environmental factors, such as vacuum, radiation, atomic oxygen, and temperature fluctuations, which can accelerate degradation. To investigate the space‐environment effect on material, changes in properties of 3D‐printed CFRPs are compared with CFRPs made through forging and conventional compression molding. Surface analyses examine morphological, chemical, and matrix composition changes, along with an evaluation of mechanical integrity. Remarkably, the naked 3D printed CFRPs withstood 8 months of LEO exposure similar to the compression molded CFRP samples, with changes in chemical properties limited to the sample's outer surface. Further, despite no protective coatings are used, limited surface erosion and no variation in mechanical strength are observed. These results provide relevant information for the development and deployment of novel 3D printed CFRPs materials for a wide spectrum of terrestrial and space applications.

Robustness analysis and station-keeping control of an interferometer formation flying mission in low Earth orbit

The impact of formation flying on interferometry is growing over the years for the potential performance it could offer. However, it is still an open field, and many studies are still required. This article presents the basic principles behind interferometry focusing first on a single array and secondly on a formation of satellites. A sensitivity analysis is carried out to evaluate how the performance of the interferometry is affected by an error in the relative position in the formation geometry. This is estimated by computing the loss of the performance in terms of percentage deviation due to a non-nominal relative trajectory, including two-dimensional errors and defining a payload index. The main goal of this study is to estimate whether some errors in the relative state are more impacting than others. The final objective is to compute the link between a position error and a specific loss of performance, to foresee the origin of the the error. Furthermore, a dynamical model is developed to describe the relative motion in the Low Earth Orbit environment, considering both the unperturbed and the J2 and drag contributions. A Proportional, Integral and Derivative controller is implemented for the position control of a multiple satellite formation flying, considering a low thrust control profile. The Formation Flying L-band Aperture Synthesis study is taken as the case scenario, analysing both nominal and non-nominal configurations. This study serves as a starting point for the development of a combined tool to assess the performance of the interferometry and the control on the relative state for future remote sensing studies involving relative motion.

IONOSPHERIC IRREGULARITIES MEASURED BY GROUND-BASED AND SATELLITE-EMBEDDED RECEIVERS: ANALYSIS OF S4 INDEX IN A LOW LATITUDE REGION

Abstract. Ionosphere is an important layer of Earth’s atmosphere which can interfere in the transmission of radio signals, affecting several activities, such as the ones related to global navigation satellite systems (GNSS) positioning. In this intend, many efforts have been made in the last decades in order to better understand and model this region of atmosphere. The observation of ionosphere and its irregularities can be performed by several techniques, including classic methods such as ionosondes. Besides that, the use of GNSS signals as source of atmospheric observations have allowed the development of different methodologies and techniques to obtain ionospheric information. Among those, the use of data collected by receivers embedded in low earth orbiting (LEO) satellites, such as the ones used in radio occultation (RO) missions can be relevant due to the amount and distribution of the data obtained. Besides that, GNSS receivers has also been used in ground stations networks to continuously monitor the ionosphere. In this sense, the present work aims to compare irregularities observed by two different techniques using data from ground-based (GNSS monitoring stations) and satellite-embedded (RO mission) receivers. The study is performed over one of the most challenging scenarios, the Brazilian region, considering seasonal variability in two months (low and high solar flux) from 2014 (solar cycle peak). The results obtained show agreement in the general behavior of the ionospheric irregularities observed by the two different techniques.

An Improved Range-Searching Initial Orbit-Determination Method and Correlation of Optical Observations for Space Debris

The Changchun Observatory of the National Astronomical Observatories, Chinese Academy of Sciences, and the Shanghai Astronomical Observatory are used to generate very short arc (VSA) angle observations of objects in low Earth orbit (LEO) and geostationary orbit (GEO) with their ground-based electrical–optical telescope arrays (EA), the Changchun EA and SAO FocusGEO, respectively. These observations are used in this paper. The range-searching (RS) algorithm for initial orbit determination (IOD) is improved through the multiple combinations of observations and the dynamic range-searching step length. Two different computation modes (the normal mode and the refining mode) of the IOD computation process are proposed. The geometrical method for the association is used. The IOD and association methods are extended to the real optical observations for both LEO and GEO objects. The results show that the IOD success rate of arcs from the LEO objects is about 91%, the error of the semimajor axis (SMA) of the initial orbital elements is less than 50 km, and the correlation accuracy rate is about 89%. The IOD success rate of arcs from the GEO objects is higher than 88%, and the correlation accuracy rate is greater than 87%. The recent COSMOS 1408 antisatellite test (ASAT) generated a large amount of debris. The algorithm of this paper and the observations of Changchun EA are used to initially identify new debris, possibly from the ASAT through initial orbit determination and track association. Finally, 64 suspected new pieces of debris can be found. The results show the effectiveness of the IOD and the correlation algorithm, as well as the potential application of the optical–electrical array in studying space events.

Influence of Different Neutral Gas Irradiation in Low Earth Orbit on the Structure and Tribological Performance of WS2 Films

Influence of Different Neutral Gas Irradiation in Low Earth Orbit on the Structure and Tribological Performance of WS2 Films

Development of artificial Earth satellite simulation software for future radio telescopes in Indonesia

"In the near future, four radio telescopes will be installed in Indonesia. Besides the astronomical purposes, these telescopes are expected to support the ground station for tracking the Artificial Earth Satellites (AES). In this study, we focus on the development of AES simulation software, named AESSIMS, that can be used to aid Indonesian radio telescope engineers in tracking the AES. This software is interactive and web-based. It can track the AES position in real time as well as predict the position for the near future. This software provides information about when a satellite signal can be acquired and lost, which can be beneficial for radio telescopes to establish communication with the satellite. We visualize the use of this software by conducting a simulation of satellite tracking by Indonesian future radio telescopes. Three Indonesian satellites named LAPAN-A1/TUBSAT, LAPAN-A2/ORARI, and LAPAN-A3/IPB are considered in the simulation. This study demonstrates that AESSIMS simulation results for Indonesian satellites and radio telescopes are consistent with the results obtained from already existing satellite tracking simulation software."

Material Characterization Required for Designing Satellites from Fiber-Reinforced Polymers

This review paper discusses the effect of polymers, especially thermoplastics, in environments with low earth orbits. Space weather in terms of low earth orbits has been characterized into seven main elements, namely microgravity, residual atmosphere, high vacuum, atomic oxygen, ultraviolet and ionization radiation, solar radiation, and space debris. Each element is discussed extensively. Its effect on polymers and composite materials has also been studied. Quantification of these effects can be evaluated by understanding the mechanisms of material degradation caused by each environmental factor along with its synergetic effect. Hence, the design elements to mitigate the material degradation can be identified. Finally, a cause-and-effect diagram (Ishikawa diagram) is designed to characterize the important design elements required to investigate while choosing a material for a satellite’s structure. This will help the designers to develop experimental methodologies to test the composite material for its suitability against the space environment. Some available testing facilities will be discussed. Some potential polymers will also be suggested for further evaluation.

LEO-Assisted Aerial Deployment in Post-Disaster Scenarios Using a Combinatorial Bandit and Genetic Algorithmic Approach

This paper proposes integrating low earth orbit satellites (LEO-Sats) and multiple aerials to provide rescue services in post-disaster areas. Aerials are distributed to provide wireless connectivity to survivors and rescue workers, while LEO-Sat exhibits backhaul linkages to aerials to connect them with the closest surviving ground base station (GBS). In this context, the aerials’ deployment should maximize the total system rate while guaranteeing fairness among the served post-disaster regions within aerials’ limited battery budget and LEO-Sat’s limited bandwidth resources. Therefore, a combinatorial bandit model with arms fairness and budget constraints (CB-FBC) is proposed to address the aerials’ deployment while maintaining fairness in covering post-disaster regions within the aerials’ limited battery resources. Additionally, the aerials’ transmit communication powers and LEO-Sat’s bandwidth resources are optimized according to traffic requests of LEO-aerial linkages using a genetic algorithm (GA). By means of numerical analysis, the proposed GA shows superior performance over other naïve benchmarks.

On the mechanical behavior of carbon fiber/epoxy laminates exposed in thermal cycling environments

Carbon fiber reinforced polymer (CFRP) composites are commonly used for reflectors of artificial satellites operating in low earth orbit (LEO). The decay of the modulus of the CFRP composite varies under different thermal cycling environments, which can lead to a reduction in the accuracy of the reflector panels, affecting the transmission of signals. This paper investigates the impact of different thermal cycling conditions on the mechanical behavior of carbon fiber/epoxy laminated composites experimentally. Three kinds of thermal cycling conditions involving continuous temperature changes are employed to explore the influence of temperature range on the residual tensile and in-plane shear moduli of the laminates. Test results indicate that the upper temperature limit and the temperature span of the thermal cycling conditions jointly affect the mechanical properties of CFRP composite laminates, but the responses of the residual tensile and in-plane shear moduli are different under the variation of each temperature parameter alone. The residual tensile and in-plane shear moduli of the laminates under thermal cycling decrease with an expansion of the temperature span having the same upper limit. If the temperature span remains constant, an increase in the upper temperature limit leads to an increase in the residual tensile modulus, but a decrease in the residual in-plane shear modulus. The main damages causing the decay of residual tensile and in-plane shear moduli of unidirectional laminates were investigated by scanning electron microscopy (SEM) technology. Observations of the microscopic fracture of the material show that the post-curing reaction factor predominantly influences the residual tensile modulus of unidirectional laminates, while the fiber/matrix interface damage factor dominates the residual in-plane shear modulus of the unidirectional laminates. Furthermore, an increase in the fiber tensile modulus decreases both residual tensile and residual in-plane shear moduli. Notably, the residual in-plane shear modulus exhibits greater sensitivity to thermal cycling compared to the residual tensile modulus. The findings reported in this paper would provide valuable insights and guidance for the design and application of carbon fiber/epoxy composites subjected to thermal cycling conditions.

A Loss Differentiation Method Based on Heterogeneous Ensemble Learning Model for Low Earth Orbit Satellite Networks.

In light of the high bit error rate in satellite network links, the traditional transmission control protocol (TCP) fails to distinguish between congestion and wireless losses, and existing loss differentiation methods lack heterogeneous ensemble learning models, especially feature selection for loss differentiation, individual classifier selection methods, effective ensemble strategies, etc. A loss differentiation method based on heterogeneous ensemble learning (LDM-HEL) for low-Earth-orbit (LEO) satellite networks is proposed. This method utilizes the Relief and mutual information algorithms for selecting loss differentiation features and employs the least-squares support vector machine, decision tree, logistic regression, and K-nearest neighbor as individual learners. An ensemble strategy is designed using the stochastic gradient descent method to optimize the weights of individual learners. Simulation results demonstrate that the proposed LDM-HEL achieves higher accuracy rate, recall rate, and F1-score in the simulation scenario, and significantly improves throughput performance when applied to TCP. Compared with the integrated model LDM-satellite, the above indexes can be improved by 4.37%, 4.55%, 4.87%, and 9.28%, respectively.