Operational Satellite Research Articles

Development of the next-generation air quality prediction system in the Unified Forecast System framework: Enhancing predictability of wildfire air quality impacts

Abstract The National Oceanic and Atmospheric Administration (NOAA) has developed an advanced regional air quality prediction system (AQPS) within the Unified Forecast System (UFS) framework to improve representations of wildfire emissions and their impacts on air quality predictions. This innovative system integrates the Environmental Protection Agency’s (EPA) Community Multiscale Air Quality (CMAQ) model as a column chemistry model with the UFS-based atmospheric model, operating in an online mode. The calculation of wildfire gas and particulate emissions relies on satellite-derived fire products, high-resolution Regional Hourly Advanced Baseline Imager (ABI) and Visible Infrared Imaging Radiometer Suite (VIIRS) Emissions (RAVE). A period in June and July 2023 with Quebec Canadian wildfires, which severely impacted air quality in the United States (US), was chosen as a case study to assess the predictive capability of the UFS-AQM system. The UFS-AQM predictions of fine particulate (PM2.5) and ozone (O3) were evaluated against AirNow observations from June 15 to July 14, 2023. The results indicate a substantial improvement in PM2.5 predictions when compared to the previous operational forecast. Meanwhile, the system demonstrates a strong ability of predicting O3 exceedance events during the dissipation phase of the wildfire. Furthermore, the online system shows more realistic predictions of aerosol optical depth (AOD) as compared to the previous operational forecast and satellite retrieval data. Finally, this study outlines a plan for further advancing a comprehensive regional AQPS at NOAA.

A Unified Resource Allocation Framework and Impact Evaluation for NGSO Satellite Constellations

ABSTRACTThe new era of satellite communications will rely on thousands of highly flexible spacecraft capable of autonomously managing constellation resources, such as power or frequency. Previous work has focused on the automation of the individual tasks that compose the resource allocation problem (RAP). However, two aspects remain unaddressed: (1) A unified method that autonomously solves the RAP under nongeosynchronous conditions is still to be developed, and (2) the cost–benefit of using optimization methods remains to be studied. Note that these studies are critical for satellite operators to take appropriate decisions concerning the automation of communications constellations operations. To close this gap, this work proposes an adaptive framework to solve the RAP for high‐dimensional nongeosynchronous satellite constellations. The proposed framework uses a divide‐and‐conquer approach that solves each step of the RAP, leveraging different optimization algorithms at the subproblem level to produce a valid and efficient allocation of resources over long time horizons. When comparing the proposed method against scalable greedy solutions, the former achieves up to four times more constellation capacity and reduces the overall consumed power by up to a factor of 3. The cost–benefit analysis reveals which RAP subproblems should be prioritized depending on the operator's objectives. Studying diverse operational conditions, we find that optimization methods enhance capacity consistently yet might raise power consumption due to trade‐offs in the routing algorithms.

Synthetic satellite telemetry data for machine learning

AbstractFor many machine learning tasks, labeled data are crucial. Even though there are methods that can be trained with data with only few labels, most of the tasks require many labels. In satellite operations, a huge amount of data are generated by the telemetry parameters of a satellite that keep track of its status. Modern satellites collect telemetry data of thousands of parameters. For example, the GRACE Follow-On satellites, operated by the German Space Operations Center (GSOC) at the German Aerospace Center (DLR), define about 80,000 unique housekeeping parameters each. However, all these telemetry data lack a complete/holistic set of labels. These data are usually unpredictable, hard to reproduce, and very diverse. As a consequence, expert knowledge is necessary to label these data, e.g., with anomalies. Moreover, labeling data by hand can be very time-consuming and, therefore, expensive. To overcome these obstacles, we implemented a synthetic satellite telemetry data library that is able to (a) generate a large variety of telemetry-like data, (b) add a plethora of well-defined anomalies to these data, and (c) deliver the labels for these injected anomalies. With these data, we are now able to train, validate, and test our machine learning models. Furthermore, we can compare different models with reproducible data. Since satellite telemetry data are often strictly confidential, we can share these synthetic data easily with our research partners.

Research on F10.7 Index Prediction Based on Factor Decomposition and Feature Enhancement

The F10.7 index is crucial for assessing solar activity, significantly impacting communication, navigation, and satellite operations. The intrinsic complexity and variability of solar activity often result in sudden perturbations in the F10.7 index, compromising the accuracy and stability of forecasts. To address this challenge, we propose a novel prediction strategy that separately forecasts fundamental trends driven by the medium-to-long-term evolution of the solar cycle and the 27 day rotational modulation, along with transient disturbances caused by solar flares and the rapid evolution of active regions. These forecasts are then integrated to enhance overall prediction accuracy. We incorporate additional features such as the soft X-ray flare index (FISXR), magnetic type of the active region (new_Mag), and X-ray background flux (XBF) to enhance the understanding of the underlying physical processes of solar activity. Our experiments, conducted using advanced forecasting models on the SG-F10.7-All data set, validate the efficacy of our proposed strategy. Notably, the iTransformer model demonstrates superior performance in both short-term and medium-term forecasting scenarios. The inclusion of FISXR, new_Mag, and XBF significantly improves forecasting accuracy, highlighting their importance in improving the F10.7 index predictions. Our method outperforms international models from the Space Weather Prediction Center, British Geological Survey, and Collecte Localisation Satellites, exhibiting greater accuracy and adaptability across various solar activity phases. This finding provides a novel approach for precise forecasting of the F10.7 index.

Operational satellite cloud products need local adjustment – The Galapagos case of ecoclimatic cloud zonation

Operational satellite cloud products need local adjustment – The Galapagos case of ecoclimatic cloud zonation

Heat management solutions for the space camera: From design to orbital operations

Heat management solutions for the space camera: From design to orbital operations

Design And Development of a Robotic Arm for Space Debris Mitigation Using Electrostatic and Gecko-Inspired Gripping Technologies

As space debris poses a growing threat to satellite operations, there is an urgent need for advanced robotic systems capable of effective debris capture in low Earth orbit. This paper presents the development and optimization of a robotic arm equipped with an electrostatic adhesion mechanism, designed specifically for microgravity environments. The primary objective is to engineer a versatile, lightweight robotic arm that can securely capture and hold various types of debris, including non-magnetic and composite materials. Key features include electrostatic adhesive pads for adaptable grip, a telescopic extension arm to increase reach with minimal mechanical complexity, and a retractable storage profile to streamline debris retrieval and handling. Through detailed calculations, we establish the required adhesive force to counter both inertial and gravitational forces acting on debris, ensuring secure capture even during minor satellite manoeuvres. An electrostatic charging system is designed to induce sufficient adhesive force, with calculations for charge requirements and pad dimensions optimized for secure adhesion. This paper details the design, force calculations, and component selection that make the robotic arm efficient, lightweight, and adaptable, contributing to safer, more effective space debris removal.

Total Ionizing Dose Measured With the Radiation Dosimeter Onboard the FY‐3E Satellite

AbstractFengYun‐3E (FY‐3E) was the first operational meteorological satellite in China in early morning orbit. The radiation dosimeter, which is part of the satellite's Space Environment Monitor (SEM), contains three probes to measure the total ionizing dose in the three directions of the satellite. Improvements in the dosimeter have been made to increase detection sensitivity. The RADFET, a radiation dose sensor, was calibrated using 60Co radionuclide source to correlate its threshold voltage shift with the total ionizing dose. The improved dosimeter has a sensitivity of 0.06 rad (Si) to 0.45 rad (Si) in the measurement range. The flight data showed that the total ionizing dose within the FY‐3E satellite is anisotropic. The radiation dose rate in the +X and +Y directions increased by a few factors after the geomagnetic storms.

Evaluation and Anomaly Detection Methods for Broadcast Ephemeris Time Series in the BeiDou Navigation Satellite System.

Broadcast ephemeris data are essential for the precision and reliability of the BeiDou Navigation Satellite System (BDS) but are highly susceptible to anomalies caused by various interference factors, such as ionospheric and tropospheric effects, solar radiation pressure, and satellite clock biases. Traditional threshold-based methods and manual review processes are often insufficient for detecting these complex anomalies, especially considering the distinct characteristics of different satellite types. To address these limitations, this study proposes an automated anomaly detection method using the IF-TEA-LSTM model. By transforming broadcast ephemeris data into multivariate time series and integrating anomaly score sequences, the model enhances detection robustness through data integrity assessments and stationarity tests. Evaluation results show that the IF-TEA-LSTM model reduces the RMSE by up to 20.80% for orbital parameters and improves clock deviation prediction accuracy for MEO satellites by 68.37% in short-term forecasts, outperforming baseline models. This method significantly enhances anomaly detection accuracy across GEO, IGSO, and MEO satellite orbits, demonstrating its superiority in long-term data processing and its capacity to improve the reliability of satellite operations within the BDS.

Enhanced Space Debris Detection and Monitoring Using a Hybrid Bi-LSTM-CNN and Bayesian Optimization

Space debris detection is important to the integrity of space missions and satellites, especially with the increase in the number of satellites and spacecraft in orbit. This paper addresses this by a new concept innovative approach using hybrid Bi-LSTM-CNN architecture which is optimized using Bayesian Optimization. The study presents an analysis approach based on the whole combination of machine learning and deep learning, a high-quality space debris detector, that can identify both the kind of object and the size of its RCS. The new method goes beyond what we have done so far and shows better results on a wide range of evaluation parameters, such as accuracy, precision, memory, and F1 score. Also, the study takes up the pragmatic issue of training time, thereby ensuring performance in real time. Esthetic trials on real datasets confirm the fit of the hybrid model, sensitivity, and efficacy with 99.16% and 99.98% detection and prediction of space debris types, respectively. In summary, this paper makes space debris tracking much more robust and mitigates threats associated with spaceflight and satellite operations, but they can offer a lot of information on threats and mitigation measures. The findings suggest that this hybrid model could be augmented with current space debris tracking systems, to increase their predictive power and operational effectiveness. Received: 2 July 2024 | Revised: 15 August 2024 | Accepted: 6 September 2024 Conflicts of Interest The author declares that she has no conflicts of interest to this work. Data Availability Statement The datasets cited in this manuscript are publicly available and can be accessed from the original sources referenced in the text. The data that support the findings of this study are openly available in Kaggle at https://www.kaggle.com/datasets/kandhalkhandeka/sate llites-and-debris-in-earths-orbit/data. No additional data were generated or analyzed during the current study Author Contribution Statement Ishaani Priyadarshini: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition.

Evaluation of Satellite-Derived Atmospheric Temperature and Humidity Profiles and Their Application as Precursors to Severe Convective Precipitation

This study evaluated the reliability of satellite-derived atmospheric temperature and humidity profiles derived from occultations of Fengyun-3D (FY-3D), the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), the Meteorological Operational Satellite program (METOP), and the microwave observations of NOAA Polar Orbital Environmental Satellites (POES) using various conventional sounding datasets from 2020 to 2021. Satellite-derived profiles were also used to explore the precursors of severe convective precipitations in terms of the atmospheric boundary layer (ABL) characteristics and convective parameters. It was found that the satellite-derived temperature profiles exhibited high accuracy, with RMSEs from 0.75 K to 2.68 K, generally increasing with the latitude and decreasing with the altitude. Among these satellite-derived profile sources, the COSMIC-2-derived temperature profiles showed the highest accuracy in the middle- and low-latitude regions, while the METOP series had the best performance in high-latitude regions. Comparatively, the satellite-derived relative humidity profiles had lower accuracy, with RMSEs from 13.72% to 24.73%, basically increasing with latitude. The METOP-derived humidity profiles were overall the most reliable among the different data sources. The ABL temperature and humidity structures from these satellite-derived profiles showed different characteristics between severe precipitation and non-precipitation regions and could reflect the evolution of ABL characteristics during a severe convective precipitation event. Furthermore, some convective parameters calculated from the satellite-derived profiles showed significant and rapid changes before the severe precipitation, indicating the feasibility of using satellite-derived temperature and humidity profiles as precursors to severe convective precipitation.

The state of Earth Observing system today: updates compiled from recent EUMETSAT Meteorological Satellite Conferences

Abstract This work presents highlights from the 2021 and 2022 EUMETSAT conferences, drawn from their presentations, posters and panel discussions and placed into the wider context of the global Earth Observing (EO) system. These highlights collectively reveal much about the current state of knowledge about the EO system, its potential future evolutions and how that system may be used to produce useful products and services. European, American and Asian space agencies presented their visions for the next generation of operational satellite programmes and demonstrated how these will continue to improve environmental forecasting and monitoring products. User communities presented updates in the use of satellite data, including climate records, novel precipitation retrievals, drought monitoring, weather forecasting and retrievals of a broadening range of trace gases. On the technology side, discussion on the impact of Artificial Intelligence (AI) for Earth observation was a major theme, particularly for weather forecasting, data assimilation or other environmental predictions. Cloud computing was another topic due to its potential to streamline the workflow of EO scientists, enhancing collaborations and unlocking access to previously-unavailable data or computing resources. Finally, discussion on the miniaturization of observational instruments was another major theme of both conferences, highlighting both the possibility of novel or enhanced observations and the emerging economic case for commercial entities to operate fleets of meteorological satellites.

Enabling efficient satellite mission design with rule-based collision avoidance

The growing number of operational spacecraft in Earth's orbit entails an increasing operational effort for collision avoidance (COLA), particularly regarding the coordination of evasive measures. To reduce the associated workload, COLA operations should already be considered in the early planning phases of space missions. The Mission Analysis Software (MAS) is a web-based application developed within the ESA-funded CASCADE (Collision avoidance, satellite coordination assessment demonstration environment) project by OKAPI:Orbits and TU Darmstadt for this purpose. The software follows a data-driven approach to offer satellite operators, mission designers, service providers, agencies, and authorities two services: conjunction assessment and rule analysis. The conjunction assessment provides an estimation of the number and type of conjunctions to be expected on the targeted orbit and identifies frequently conjuncting parties for the current population of active satellites as well as for conceivable future scenarios. The rule analysis follows a rule-based approach to coordinate COLA between individual operators, allowing users to build custom hierarchical rule sets from pre-defined rule building blocks to achieve a desired split of effort between the conjunction parties. The MAS enables the assessment of the operational consequences for a chosen rule set, empowering users to reach bilateral agreements with identified frequently conjuncting parties to determine the obligation to take evasive measures for future conjunctions. The approach of the MAS allows for the pre-emptive reduction of the expected number of conjunctions enabling operators to optimize orbit parameters within their mission constraints as well as the automatization of COLA coordination during operations. Through this, the MAS optimizes propellant needs, mission time, and required workforce associated with COLA for space missions.This paper presents the MAS, showcasing the key features and use cases that have been developed closely with stakeholders and the European Space Agency. Furthermore, the data-based simulation approach of the MAS will be explained, covering the data sources and design choices for the conjunction detection and propagation module. The paper also presents the results of a preliminary rule analysis conducted for the population of active satellites in low Earth orbit as of April 2023. As an intermediate result of an on-going research activity involving the authoring entities, a major goal of this paper is to engage with satellite operators, mission designers, service providers, agencies, and authorities in order to tailor the results of the activity to their actual needs.

Comparisons of Energetic Electron Observations Between FIREBIRD‐II CubeSats and POES/MetOp Satellites From 2018 to 2020

AbstractPrecipitation into the atmosphere is one of the main processes by which high energy electrons trapped in Earth's inner magnetosphere are lost from the system. Precipitating electrons can affect the chemical composition of the atmosphere and provide insight into the complex dynamics of the Van Allen radiation belts. This study compares energetic electron precipitation measurements at low‐Earth‐orbit by the Focused Investigations of Relativistic Electron Burst Intensity, Range, and Dynamics (FIREBIRD‐II) CubeSats with NOAA Polar‐orbiting Operational Environmental Satellite (POES) and ESA Meteorological Operational satellite (MetOp) satellites, which are equipped with the Medium‐Energy Proton Electron Detector (MEPED). The analysis considers 51 high quality conjunction events at >300 keV during times of low to moderate geomagnetic activity. The spacecraft capture similar electron flux variability, and FIREBIRD‐II observations fall between POES/MetOp and telescopes, likely a result of FIREBIRD‐II sampling both precipitating and mirrored electrons due to uncertainties in pointing direction. Results demonstrate the value of high‐resolution differential energy observations of electron precipitation by low‐cost CubeSats such as FIREBIRD‐II, especially during periods of low flux.

Optimization of a handheld line launcher for microgravity utility and rescue tasks

Line launchers are devices that have been used for centuries for maritime rescue operations. The typical implementation is the use of a gun, rocket, or mechanical launcher to hurl a grappling hook or flotation buoy for stranded ships and overboard sailors. Microgravity offers analogous use cases, ranging from microsatellite operations to space debris interception. As such, the Lachesis line launcher is a handheld device that is purpose-built for microgravity applications. After the user pulls the trigger, a laser ignites a smoothbore rocket-propelled projectile which carries a nylon line behind it. Angled threads in the barrel provide the spin and stability that is typically only achieved by conventional rifling. To reduce weight, most components are 3D-printed out of polylactic acid (PLA), a biodegradable and light plastic. With a total weight of 68 g and a projectile kinetic energy of 0.127 J, the Lachesis line launcher presents an effective, potential option, even with contemporary operational constraints. The design combines several proven principles to demonstrate the viability and use case for an updated line launcher in orbital operations. KEY WORDS: line launcher, microgravity, rescue device, object capture

Preface

Abstract We are pleased to present the proceedings of the International Conference on Space Weather and Satellite Application (ICeSSAT) 2024, held from 23rd August 2024 to 25th August 2024 at Universiti Sultan Zainal Abidin (UniSZA), Terengganu, Malaysia. The conference brought together leading researchers, educators, and professionals from various fields to discuss recent advancements in the fields of space science and satellite technologies. These proceedings compile a wide range of contributions that reflect the latest innovations, trends, and challenges in the related fields offering insights into both theoretical and practical applications. The theme of ICeSSAT 2024, “Space Weather and Satellite,” highlights the critical importance of space weather monitoring and satellite applications in today’s rapidly evolving technological landscape. As space weather phenomena continue to impact satellite operations, telecommunications, and navigation systems, the research and discussions presented at this conference address the urgent need for resilient and adaptable solutions. The papers included in this volume were selected through a rigorous double-blind peer-review process, ensuring the highest quality and relevance. We extend our gratitude to the reviewers for their time and effort in evaluating the submissions and providing valuable feedback to the authors. We would also like to thank the authors and presenters for their significant contributions to this body of knowledge, which form the foundation of this proceedings volume. Their work not only advances knowledge in the field but also opens new pathways for future research and collaboration. List of Editorial Board, Acknowledgements and Organizing Committees are available in this Pdf.

Surface Charging Analysis of Ariel Spacecraft in L2-Relevant Space Plasma Environment and GEO Early Transfer Orbit

Ariel (Atmospheric Remote-sensing Infrared Exoplanet Large-survey) is the ESA Cosmic Vision M4 mission, selected in March 2018 and officially adopted in November 2020, whose launch is scheduled by 2029. It aims at characterizing the atmospheres of hundreds of exoplanets orbiting nearby stars by low-resolution primary and secondary transit spectroscopy. The Ariel spacecraft’s operational orbit is baselined as a large-amplitude, eclipse-free halo orbit around the second Lagrangian (L2) point, a virtual point located at about 1.5 million km from the Earth in the anti-Sun direction, as it offers the possibility of long uninterrupted observations in a fairly stable radiative and thermo-mechanical environment. A direct escape injection with a single passage through the Van Allen radiation belts is foreseen. During both the injection trajectory and the final orbit around L2, Ariel will be immersed in and interact with Sun radiation and the plasma environment. These interactions usually result in the accumulation of net electrostatic charge on the external surfaces of the spacecraft, leading to a potentially hazardous configuration for the nominal operation and survivability of the Ariel platform and its payload, as it may induce harmful electrostatic discharges (ESDs). This work presents the latest results collected from surface charging analyses conducted using the SPIS tool of the European SPINE community along the GEO insertion orbit segment and operational orbit.

A low earth orbit satellite descent strategy

The object of the article is the method of descending a satellite from low Earth orbit (LEO) at the end of its service lifetime for its disposal. The main problem is to ensure a safe and cost-effective disposal of the satellite while minimizing risks to the environment and other objects in orbit. Based on the method, calculations were made for lowering the orbit and directing the satellite to a remote area of the Earth’s ocean. The calculations included braking pulses, fuel consumption, descent time to the burial orbit, and the time for natural descent before reaching the Earth's surface. The descent process is divided into three stages: active descent using low-thrust engines (LTE), passive descent due to natural braking in the out-of-atmosphere part, and fall through the dense atmosphere. Dependency graphs were provided to illustrate orbit altitude, satellite speed, reentry angle changes, and flight range over time. The findings revealed that combining active orbital maneuvers with passive orbital decay optimizes the deorbiting procedure by minimizing fuel requirements and operational complexity. The proposed strategy ensures the satellite-controlled re-entry and safe disposal, significantly reducing the risks of collisions and environmental impact. The results solved the problem by defining a staged satellite descent process. Duration were computed for active descent with braking impulses for uniform altitude reduction and passive descent due to atmospheric drag. The trajectory and duration of fall in atmosphere. The process ensures controlled re-entry and safe disposal. This method is suitable for satellite operators and space agencies handling LEO missions

Extended Symmetry of Higher Painlevé Equations of Even Periodicity and Their Rational Solutions

The structure of the extended affine Weyl symmetry group of higher Painlevé equations of N periodicity depends on whether N is even or odd. We find that for even N, the symmetry group A^N−1(1) contains the conventional Bäcklund transformations sj,j=1,…,N, the group of automorphisms consisting of cycling permutations but also reflections on a periodic circle of N points, which is a novel feature uncovered in this paper. The presence of reflection automorphisms is connected to the existence of degenerated solutions, and for N=4, we explicitly show how even reflection automorphisms cause degeneracy of a class of rational solutions obtained on the orbit of the translation operators of A^3(1). We obtain the closed expressions for the solutions and their degenerated counterparts in terms of the determinants of the Kummer polynomials.

Review on Semi-Autonomous Robots for Satellite Maintenance and Refueling

As the number of satellites in Earth's orbit continues to grow, the need for efficient satellite servicing solutions becomes increasingly pressing. Currently, about 9,900 satellites are in orbit, with over 3,300 of these being inactive, posing a threat as space debris. Traditional methods for satellite maintenance and refueling are complex, expensive, and risky. The development of semi-autonomous robots, powered by advancements in artificial intelligence and robotics, presents a more efficient alternative. These robots can perform complex maintenance and refueling tasks with minimal human intervention, reducing costs and risks associated with satellite servicing. This paper investigates the design, technological advancements, and operational strategies behind these robots, and how they can mitigate space debris while enhancing the sustainability of satellite operations. Key Words: Maintenance, Satellites, Refuelling, Robots.