Operational Satellite Research Articles

Characterization of Bias in Fengyun-4B/AGRI Infrared Observations Using RTTOV

As China’s first operational second-generation geostationary satellite, Fengyun-4B carries the newly developed Advanced Geostationary Radiation Imager (AGRI), which adds a low-level water vapor detection channel and an adjusted spectrum range of four channels to improve the quality of observation. To characterize biases of the infrared (IR) channels of Fengyun-4B/AGRI, RTTOV was applied to simulate the brightness temperature of the IR channels during the period of Fengyun-4B trial operation (from June to November 2022) under clear-sky conditions based on ERA5 reanalysis, which may provide beneficial information for the operational applications of Fengyun-4B/AGRI, such as data assimilation and severe weather monitoring. The results are as follows: (1) due to the sun’s influence on the satellite instrument, the brightness temperature observations of the Fengyun-4B/AGRI 3.75 μm channel were abnormally high around 1500 UTC in October, although the data producer made efforts to eliminate abnormal data; (2) the RTTOV simulations were in good agreement with the observations, and the absolute mean biases of the RTTOV simulations were less than 1.39 K over the ocean, and less than 1.77 K over land, for all IR channels under clear-sky conditions, respectively; (3) for the variation of spatial distribution bias over land, channels 12–15 were more obvious than channels 9–11, which indicates that the skin temperature of ERA-5 reanalysis and surface emissivity may have greater spatial uncertainty than the water vapor profile; (4) the biases and standard deviations of Fengyun-4B/AGRI channels 9–15 had negligible dependence on the satellite zenith angles over the ocean, while the standard deviation of channels 8 and 12 had a positive correlation with satellite zenith angles when the satellite zenith angles were larger than 30°; and (5) the biases and standard deviations of Fengyun-4B/AGRI IR channels showed scene brightness temperature dependence over the ocean.

Contract Structures for SatCom: How Will Competition from Low Earth Orbit Mega Constellations Change How Communications Services Are Purchased?

Communication satellite operators contract their capacity through service-level agreements (SLAs) to their customers, some of which reserve fixed capacity over multiple years. Relative to current capacity constraints, this market has seen substantial demand growth, as well as number of new entrants such as SpaceX and Amazon. While historically these SLAs have helped matched large capital investments with long-term revenue, the history of communications markets suggests that this leaves significant capacity and revenues underutilized. Our objectives were to review existing SLAs, identify their limitations, and explore new SLAs, some of which leverage the flexibility of new communication satellites. We find that existing SLAs can be characterized into classic, data volume, and dual SLAs. While important historically, these are found to leave significant capacity and revenue potential underutilized while simultaneously failing to meet customer desire for improved flexibility and lower prices. Through 60 interviews with SatCom customers, we find that lower prices and more flexibility for capacity bookings are the 2 most desired characteristic. By examining the history of the cloud computing and telecommunication industries, we propose spot instance, time-of-day pricing, and 2 classes of service SLAs, which address these shortcomings by offering more liquid services accessible to a broader range of customers. We conclude that the classic SLA excels where reliability and speed are essential, traffic volume is high, and variation is low. When consumers are price-sensitive, data volume SLAs, time-of-day pricing SLAs, and 2 classes of service SLAs are affordable options. When the traffic patterns are not repeating on a daily or monthly basis, spot instances offer the desired flexibility.

Canadian Fire Management Agency Readiness for WildFireSat: Assessment and Strategies for Enhanced Preparedness

Wildfires are worsening in Canada and globally, partly due to climate change. The government of Canada is designing and building WildFireSat, the world’s first purpose-built operational satellite system for wildfire monitoring. It will provide new fire intelligence to support decision-making. It takes time for fire management agencies to use new information: to understand it and its implications, change processes, develop training, and modify computer systems. Preparing for the system’s prelaunch will allow agencies to benefit more rapidly from the new information. We present (1) an assessment of the readiness of 12 Canadian fire management agencies to integrate WildFireSat information and (2) guidance for reducing readiness gaps. We used survey and other data to score readiness indicators for three readiness components: understanding, organization, and information technology. We weighted the influence of each indicator score on each component. We modelled scoring and weighting uncertainties and used Monte Carlo simulation to generate distributions of aggregated agency readiness. The results indicated that most agencies have a moderate level of readiness while others have a higher level of readiness. Cluster analysis was used to group agencies by similarity in multiple dimensions. Strategies for increasing readiness are highlighted. This identifies opportunities for agencies and the WildFireSat team to collaborate on enhancing readiness for the forthcoming WildFireSat data products.

Design Optimization of Space Debris Decent Trajectory Considering Land Security by Evolutionary Calculation

Space debris is artifacts that are dumped into orbit at the end of satellite operations or at the time of rocket launch, and is increasing in number as space exploration becomes more active. Since space debris poses a risk of collision in orbit during the launch of new spacecraft, studies on debris disposal have been active. In addition, orbit design is required so that debris can be disposed of at sea, avoiding land, where unburned debris can cause human and material damage due to the possibility of falling debris. Because debris cannot be actively controlled, it is required to predict the optimal trajectory before the re-entry and to consider the timing and the acceleration for the re-entry. In this report, we simulated the debris trajectory from the re-entry to reaching at the ground surface, and applied the evolutionary algorithm for the maximization of the distances from the reaching offshore point to the nearest coastline, considering as a risk of the ground.

4DEnVar-based inversion system for ammonia emission estimation in China through assimilating IASI ammonia retrievals

Atmospheric ammonia has been hazardous to the environment and human health for decades. Current inventories are usually constructed in a bottom-up manner and subject to uncertainties and incapable of reproducing the spatiotemporal characteristics of ammonia emission. Satellite measurements, for example, Infrared Atmospheric Sounder Interferometer (IASI) and Cross-Track Infrared Sounder, which provide global coverage of ammonia distribution, have gained popularity in ammonia emission estimation through data assimilation methods. However, satellite-based emission inversion studies on China are limited. In this study, we propose a four-dimensional ensemble variational-based ammonia emission inversion system to optimize ammonia emissions in China. It was developed by assimilating the IASI ammonia retrievals onboard Meteorological Operational satellite A and B into a chemical transport model Goddard Earth Observing System Chemical model (GEOS-Chem). Monthly inversion experiments were conducted in April, July, and October 2016 to test the performance. The inversion result indicated that the prior inventory from the MEIC model captured ammonia spreads in general; however, it heterogeneously underrated the emission intensity. The increments obtained in the assimilation were as high as 50% in North, East, and Northwest China. The posterior emission inventory presented a regional emission flux consistent with relevant studies. Driven by the optimized source estimate, GEOS-Chem provides superior results than using the prior in the evaluation of the assimilated IASI retrievals and the surface ammonia concentration measured by the ground-based Ammonia Monitoring Network in China.

Machine learning-based approach for ballistic coefficient estimation of resident space objects in LEO

The increasing number of Resident Space Objects poses a serious threat to the safe operation of satellites. Alongside with mitigation policies, it is fundamental to predict the trajectories of such objects which requires the accurate estimation of the physical characteristics that influence their orbits. An important role is played by the area-to-mass ratio, i.e., the ratio between the area exposed to the atmosphere/the Sun and the mass of the space object for the LEO/MEO and GEO region. Current literature proposes several approaches for the estimation of the area-to-mass ratio, ranging from semi-analytical to numerical methods. As regards the latter category, recent studies have focused on classification or regression algorithms for specific types of orbits (e.g., sun-synchronous, geostationary).In this context, this paper proposes a machine learning-based regression approach for the estimation of the ballistic coefficient (i.e., the product between the drag coefficient and the area-to-mass ratio) in Low Earth Orbit, covering a wide set of orbital parameters. Using a synthetic space catalogue, the performance of different types of machine learning techniques is evaluated and compared. A sensitivity analysis is carried out to analyse the effect on performance of the number of trainings, the propagation time, the number of objects of the training data set, and the frequency of the measurements. The applicability of the presented approach is tested and discussed using both real (i.e., based on publicly available catalogues of Two-Line Elements) and synthetic datasets.

Dressed jeff-1/2 objects in mixed-valence lacunar spinel molybdates

The lacunar-spinel chalcogenides exhibit magnetic centers in the form of transition-metal tetrahedra. On the basis of density-functional computations, the electronic ground state of an Mo413+ tetrahedron has been postulated as single-configuration a12 e4 t25, where a1, e, and t2 are symmetry-adapted linear combinations of single-site Mo t2g atomic orbitals. Here we unveil the many-body tetramer wave-function: we show that sizable correlations yield a weight of only 62% for the a12 e4 t25 configuration. While spin–orbit coupling within the peculiar valence orbital manifold is still effective, the expectation value of the spin–orbit operator and the g factors deviate from figures describing nominal t5jeff = 1/2 moments. As such, our data documents the dressing of a spin–orbit jeff = 1/2 object with intra-tetramer excitations. Our results on the internal degrees of freedom of these magnetic moments provide a solid theoretical starting point in addressing the intriguing phase transitions observed at low temperatures in these materials.

Homomorphism obstructions for satellite maps

A knot in a solid torus defines a map on the set of (smooth or topological) concordance classes of knots in S 3 S^3 . This set admits a group structure, but a conjecture of Hedden suggests that satellite maps never induce interesting homomorphisms: we give new evidence for this conjecture in both categories. First, we use Casson-Gordon signatures to give the first obstruction to a slice pattern inducing a homomorphism on the topological concordance group, constructing examples with every winding number besides ± 1 \pm 1 . We then provide subtle examples of satellite maps which map arbitrarily deep into the n n -solvable filtration of Cochran, Orr, and Teichner [Ann. of Math. (2) 157 (2003), pp. 433–519], act like homomorphisms on arbitrary finite sets of knots, and yet which still do not induce homomorphisms. Finally, we verify Hedden’s conjecture in the smooth category for all small crossing number satellite operators but one.

Spectral features of ocean colour radiometric products in the presence of cyanobacteria blooms in the Baltic Sea

Cyanobacteria blooms are recurrent in the Baltic Sea with frequency and intensity increasing with temperature. By relying on autonomous multispectral measurements from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC), this study exploited an unprecedented dataset of in situ remote sensing reflectance RRS(λ) spectra (with wavelength λ in the interval 400–667 nm) acquired during filamentous cyanobacteria blooms in the Baltic Sea. The study investigated the temporal evolution of the in situ RRS(λ) during these blooms with particular emphases on those spectral features that may show potential to identify cyanobacteria and their development stages. Additionally, it assessed operational satellite Ocean Colour RRS(λ) products from the Ocean and Land Colour Instrument (OLCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) in the presence of cyanobacteria, for which only qualitative evaluations are available from previous studies. To ascertain to what extent satellite operational data products could be used for cyanobacteria detection in the Baltic Sea, the comparison of in situ and satellite derived RRS(λ) showed poor agreement with differences particularly pronounced at the blue centre-wavelengths. Nevertheless, band-differences in the green-red spectral region for OLCI and for MODIS exhibited less dependence on atmospheric correction issues with mean absolute relative differences between 8.3% and 9.6% for OLCI and between 12.6% and 12.9% for MODIS in the presence of cyanobacteria. Additionally, they showed potential to indicate the presence and development stage of cyanobacteria blooms in Baltic Sea waters while not being sensitive to other algal blooms.

Satellite and Terrestrial Network Convergence on the Way Toward 6G

Compared with traditional satellite communication systems, the recent advancement by 5G non-terrestrial network (NTN) technology offers a disruptive solution by enhancing mobile cellular technology to support satellite communications. It allows satellite operators to leverage the mobile cellular ecosystem and its economies of scale to penetrate satellite communications from a niche market to mainstream consumer market. On the other hand, it also facilitates the integration between the networks operated by terrestrial and satellite operators via the common radio/core network technology and architecture. With the key enabler by multi-mode devices, which could flexibly switch between terrestrial and satellite networks, NTN technology can turn terrestrial and satellite operators from competitors toward partners (e.g., complement service coverage, traffic roaming, and service platform). It is generally believed that satellite and terrestrial network convergence will be a mega trend from 5G toward 6G. The following sections will further investigate the potential use cases and advantages.

Annular Khovanov homology and meridional disks

We exhibit infinite families of annular links for which the maximum nonzero annular Khovanov grading grows infinitely large but the maximum nonzero annular Floer-theoretic gradings are bounded. We also show this phenomenon exists at the decategorified level for some of the infinite families. Our computations provide further evidence for the wrapping conjecture of Hoste–Przytycki and its categorified analogue. Additionally, we show that certain satellite operations be used to construct counterexamples to the categorified wrapping conjecture. We also extend the Batson–Seed link splitting spectral sequence to the setting of annular Khovanov homology.

Future Space Networks: Toward the Next Giant Leap for Humankind

Due to the unprecedented advances in satellite fabrication and deployment, innovative communications and networking technologies, ambitious space projects and programs, and the resurgence of interest in satellite networks, there is a need to redefine space networks (SpaceNets) to incorporate all of these evolutions. This paper introduces a vision for future SpaceNets that considers advances in several related domains. First, we present a reference architecture that captures the various network entities and terminals in a holistic manner. Based on this, space, air, and ground use cases are studied. Then, the architectures and technologies that enable the envisaged SpaceNets are investigated. In so doing, we highlight the activities and projects of different standardization bodies, satellite operators, and national organizations towards the envisioned SpaceNets. Finally, the challenges, potential solutions, and open issues from communications and networking perspectives are discussed.

An estimate of expected economic losses from satellite collisions with orbital debris

We estimate the expected annual cost of satellite collisions with orbital debris and find that the expected annual loss for all orbits was $86-103 million in 2020. Nearly all expected losses, $79-102 million, were in LEO, and these losses represent approximately 0.16% of the value of operational satellites in that orbit. Over 70% of losses occurred in the 600-900 km orbital band. Commercial satellites’ share of expected losses is approximately one-third of expected total losses. These findings may have implications for policy, in particular relating to the market for active debris removal.

Autonomous Satellite Wildfire Detection Using Hyperspectral Imagery and Neural Networks: A Case Study on Australian Wildfire

One of the United Nations (UN) Sustainable Development Goals is climate action (SDG-13), and wildfire is among the catastrophic events that both impact climate change and are aggravated by it. In Australia and other countries, large-scale wildfires have dramatically grown in frequency and size in recent years. These fires threaten the world’s forests and urban woods, cause enormous environmental and property damage, and quite often result in fatalities. As a result of their increasing frequency, there is an ongoing debate over how to handle catastrophic wildfires and mitigate their social, economic, and environmental repercussions. Effective prevention, early warning, and response strategies must be well-planned and carefully coordinated to minimise harmful consequences to people and the environment. Rapid advancements in remote sensing technologies such as ground-based, aerial surveillance vehicle-based, and satellite-based systems have been used for efficient wildfire surveillance. This study focuses on the application of space-borne technology for very accurate fire detection under challenging conditions. Due to the significant advances in artificial intelligence (AI) techniques in recent years, numerous studies have previously been conducted to examine how AI might be applied in various situations. As a result of its special physical and operational requirements, spaceflight has emerged as one of the most challenging application fields. This work contains a feasibility study as well as a model and scenario prototype for a satellite AI system. With the intention of swiftly generating alerts and enabling immediate actions, the detection of wildfires has been studied with reference to the Australian events that occurred in December 2019. Convolutional neural networks (CNNs) were developed, trained, and used from the ground up to detect wildfires while also adjusting their complexity to meet onboard implementation requirements for trusted autonomous satellite operations (TASO). The capability of a 1-dimensional convolution neural network (1-DCNN) to classify wildfires is demonstrated in this research and the results are assessed against those reported in the literature. In order to enable autonomous onboard data processing, various hardware accelerators were considered and evaluated for onboard implementation. The trained model was then implemented in the following: Intel Movidius NCS-2 and Nvidia Jetson Nano and Nvidia Jetson TX2. Using the selected onboard hardware, the developed model was then put into practice and analysis was carried out. The results were positive and in favour of using the technology that has been proposed for onboard data processing to enable TASO on future missions. The findings indicate that data processing onboard can be very beneficial in disaster management and climate change mitigation by facilitating the generation of timely alerts for users and by enabling rapid and appropriate responses.

Fixed-point results for convex orbital operators

Abstract The aim of this article is to introduce a new type of operator similar to those of A. Petruşel and G. Petruşel type (Fixed point results for decreasing convex orbital operators, J. Fixed Point Theory Appl. 23 (2021), no. 35) and prove some fixed-point theorems which generalize and complement several results in the theory of nonlinear operators.

In-Orbit FPGA reprogramming device for small satellites

Development of satellite technologies is a challenging task, which includes design, manufacturing, testing, and in-orbit operation stages. The reliability of each subsystem shall be at the highest level since space has severe environmental conditions and most satellites do not have an opportunity to perform repairment or replacement of their hardware components.In-orbit reprogramming of some devices, such as On-board Computer (OBC), Attitude Control Unit (ACU), and Power Control Unit (PCU) can provide great advantages to a mission by extending the lifetime and performance of a satellite's operation. At the same time, even a small mistake can result in a lot of monetary losses or even failure of a subsystem or the whole project. So, a reprogramming method to be used in space missions shall undergo excessive testing to provide high reliability for updating software in orbit.This paper is devoted to an investigation of available and applicable methods for remote reprogramming of Field-Programmable Gate Array (FPGA) based subsystems.A commercial off-the-shelf (COTS) single board computer (SBC) was used as a standalone subsystem to perform reprogramming of a target device. The SBC was tested extensively and reinforced for ensuring its space-compatibility. Several open-source software-based solutions were considered. Some of them are applicable to a wide range of processor architectures, including ARM. Considered methods could reconfigure an FPGA successfully with some major limitations, which were also described in the paper.Based on the investigation, Xilinx Software Command-line Tool (XSCT) was selected as a reprogramming method for ACU of the latest satellite of iQPS, QPS-SAR-2 (“IZANAMI”).

Detection and characterisation of unknown maneuvers in spacecraft

Space debris detection and characterisation is an important and pressing field, as the amount of space debris is growing due to the increase in spacecraft launches and increasing interests for space uses. Space agencies like NASA and ESA keep track of over 5,000 spacecraft and 20,000 spacecraft-related debris objects currently orbiting the Earth. An active spacecraft may undergo trajectory changes through an impulsive maneuver, or an inactive spacecraft may change its trajectory because of uncontrolled explosions due to residual fuel without warning. These pose risks to operational satellites. In addition, measurement data from tracking and detection consists of uncertainties, causing maneuver detection and characterisation methods to become computationally expensive.Thus, the goal of this work was to develop a quick, reliable, computationally inexpensive method for spacecraft maneuver detection and characterisation to be used by satellite operators and assist in collision avoidance measures. This paper presents such a technique, which is applied to simulated measurement data of an orbiting spacecraft taken from one ground site. With these objectives, a method using a modified Extended Kalman Filter (EKF) with covariance inflation from previous studies was explored and simplified. A new parameter definition is presented for maneuver detection and characterisation, named the Kaderali-parameter, or K, with focus on transverse apogee and perigee maneuvers. A relationship was then found between the parameter and the magnitude of the impulsive artificial maneuver. The method was tested in several different scenarios, varying Δv magnitude and scale, Δv direction, maneuver orbital location, orbit geometry, noise covariance, detection parameter threshold, state covariance inflation threshold, and maneuver duration.In general, it was found that as the Δv magnitude increases, the magnitude of the detection parameter also increases. This relationship was found to be a nonlinear logarithmic relationship through best fit curve testing. Possible extensions of this work in the future include: testing multi-maneuver scenarios, multi-sensor data collection and fusion, break-up or berthing events, rendezvous or mating events, and matlab EKF protocol implementation.

On Rational Solutions of Dressing Chains of Even Periodicity

We develop a systematic approach to deriving rational solutions and obtaining classification of their parameters for dressing chains of even N periodicity or equivalent Painlevé equations invariant under AN−1(1) symmetry. This formalism identifies rational solutions (as well as special function solutions) with points on orbits of fundamental shift operators of AN−1(1) affine Weyl groups acting on seed configurations defined as first-order polynomial solutions of the underlying dressing chains. This approach clarifies the structure of rational solutions and establishes an explicit and systematic method towards their construction. For the special case of the N=4 dressing chain equations, the method yields all the known rational (and special function) solutions of the Painlevé V equation. The formalism naturally extends to N=6 and beyond as shown in the paper.

Identifying key parameters impacting cost in large‐scale complex space programs using simulation‐based global sensitivity analysis

AbstractCost overruns averaging 45%–50% can occur during the acquisition process of large‐scale complex space programs. The factors that impact the cost overrun are frequently misunderstood and are not identified correctly. This paper investigates the impact of the parameters on the overall cost of a geosynchronous communication satellite program using model‐based global sensitivity analysis. A simulation model with the acquisition data was used to identify the key parameters within the system model that interact with the cost of the program. A system simulation model containing a physics‐based satellite model and a parametric cost model is utilized to conduct variance‐based sensitivity analysis. Data from selected acquisition reports are used to validate the system simulation model. Sobol' analysis is performed on the parameters associated with requirements of the satellite system, operations, and support to maintain the system, including the launch system and ground equipment. The results show that parameters related to the system‐based requirements significantly impact the program cost. These critical parameters, which influence the cost, lay the foundation to quantify the impact of system parameters and their uncertainty on the cost of the system using a simulation‐based model which will aid in the reduction of cost overruns during the design and development of future large‐scale complex engineered systems.

Application of Model-Free Control to the Operation of Post-Capture Combined Spacecraft

A model-free control method is applied to the attitude and orbital operation of the post-capture combined spacecraft, which consists of a space robot and debris. The main contribution of this paper lies in the following three aspects. Firstly, the discrete dynamic linearization method of the motion equation for a post-capture combined spacecraft is proposed, and then, the standardized expression form of multiple input and multiple output system for the attitude and orbital dynamics motions of post-capture combined spacecraft are presented. Secondly, the data mapping model of the post-capture combined spacecraft is defined, and based on this, an initial value online optimization method for the data mapping model is provided, which is key for the convergence of model-free control. Finally, a test system based on the ground-based three-axis spacecraft simulator is built to simulate the attitude and orbital operation of post-capture combined spacecraft, and the experimental system is implemented to verify the validation of the model-free control method proposed in this paper. The results show that the model-free control has a good control effect on the attitude and orbit of the post-capture combined spacecraft, even if the configuration of the spacecraft is time-varying.