Typical Satellite Research Articles

Space–ground QKD network based on a compact payload and medium-inclination orbit

Significant progress has been made in satellite-based quantum key distribution (QKD), and urgent follow-up work is to explore the optimal solution for building practical quantum constellations. Here, we demonstrate successful QKD based on the compact terminal on the Tiangong-2 Space Lab and construct a space–ground quantum network among four ground stations. The medium-inclination orbit of Tiangong-2 Space Lab can obtain multiple available passes for the same ground station in one night, increasing the key generation amount directly. Further analysis results show that the medium-inclination orbit and Sun-synchronous orbit can form good complementarity in future quantum constellations. As a comprehensive demonstration, this work takes a step toward cost-effective quantum satellites and provides a perspective for satellite constellation construction with different orbit types.

NB-IoT Random Access for Nonterrestrial Networks: Preamble Detection and Uplink Synchronization

The satellite component is recognized as a promising solution to complement and extend the coverage of future Internet of Things (IoT) terrestrial networks (TNs). In this context, a study item to integrate satellites into narrowband-IoT (NB-IoT) systems has been approved within the 3rd Generation Partnership Project (3GPP) standardization body. However, as NB-IoT systems were initially conceived for TNs, their basic design principles and operation might require some key modifications when incorporating the satellite component. These changes in NB-IoT systems, therefore, need to be carefully implemented in order to guarantee a seamless integration of both TN and nonterrestrial network (NTN) for a global coverage. This article addresses this adaptation for the random access (RA) step in NB-IoT systems, which is in fact the most challenging aspect in the NTN context, for it deals with multiuser time-frequency synchronization and timing advance for data scheduling. In particular, we propose an RA technique which is robust to typical satellite channel impairments, including long delays, significant Doppler effects, and wide beams, without requiring any modification to the current NB-IoT RA waveform. Performance evaluations demonstrate the proposal’s capability of addressing different NTN configurations recently defined by 3GPP for the 5G new radio system.

Thermal environment analysis for TianQin: II. Solar irradiance disparity across constellation

Space-borne gravitational wave (GW) detectors aim to detect GWs in low and middle frequency ranges, as a complement to the terrestrial detectors like LIGO and VIRGO. As the detectors are extremely sensitive to temperature fluctuation, great efforts have been taken to perform thermal analyses on the satellite platforms. Our previous work analysed the external thermal environment of an individual satellite for the TianQin mission. This paper raises the issue of thermal disparity across the triangular constellation. Based on optimized orbits of the TianQin, the LISA, the eLISA/NGO, and the ASTROD-GW, we evaluate the solar irradiance differences between adjacent satellites and make comparisons of the results among the missions. We subsequently introduce a universal relation to describe how orbit type and arm lengths may affect the maximum disparity. For the geocentric orbits of TianQin, we further extend the discussion on the science observation windows.

Reachable Set of Spacecraft With Finite Thrust Based on Grid Method

Reachable sets are sets of position states that the spacecraft can reach from its initial state under mass and time constraints. In this study, a method to solve the reachable set of spacecraft with finite thrust is proposed. Solving reachable sets can be transformed into solving its boundary surface using the distance fields over grids method. A grid is established to represent the boundary surface, and each node on the grid can be determined by an optimal control problem. A modified sequential convex programming with nonlinear dynamic correction is used to solve optimal control problems with a theoretical proof of convergence. Moreover, the symmetry plane of the reachable set is found to reduce the computation in applications. The method is tested with two types of orbits, namely, geosynchronous and highly elliptical orbits, and the properties of the spacecraft’s reachability in two orbits are obtained. Numerical simulations show that the proposed method can succeed in solving reachable sets under mass and time constraints in two types of initial orbits even when a long period is considered.

Dynamic Biasing for Improved On-Orbit Total-Dose Lifetimes of Commercial Electronic Devices

The survivability of microelectronic devices in ionizing radiation environments drives spacecraft design, capability, mission scope, and cost. This article exploits the periodic nature of many space radiation environments to extend device lifetimes without additional shielding or modifications to the semiconductor architecture. We propose a technique for improving component lifetimes through reduced total-dose accumulation by modulating device bias during periods of intense irradiation. Simulation of this “dynamic biasing” technique applied to single-transistor devices in a typical low-Earth orbit results in an increase in component lifetime from 114 to 477 days (318% improvement) at the expense of 5% down time (95% duty cycle). The biasing technique is also experimentally demonstrated using gamma radiation to study three commercial devices spanning a range of integrated circuit complexity in 109- and 256-rad/min dose rate conditions. The demonstrated improvements in device lifetimes using the proposed dynamic biasing technique lay a foundation for more effective use of modern microelectronics for space applications. Analogous to the role real-time temperature monitoring plays in maximizing modern processor performance, the proposed dynamic biasing technique is a means of intelligently responding to the radiation environment and capable of becoming an integral tool in optimizing component lifetimes in space.

Generic Stabilizers for Simple Algebraic Groups

We prove a myriad of results related to the stabilizer in an algebraic group G of a generic vector in a representation V of G over an algebraically closed field k. Our results are on the level of group schemes, which carries more information than considering both the Lie algebra of G and the group G(k) of k-points. For G simple and V faithful and irreducible, we prove the existence of a stabilizer in general position, sometimes called a principal orbit type. We determine those G and V for which the stabilizer in general position is smooth, or dimV/G<dimG, or there is a v∈V whose stabilizer in G is trivial.

Formula omitted] and [formula omitted] axi-symmetric horseshoe periodic orbits about Lagrangian points: A global grid search approach

This paper presents the numerical exploration of planar as well as spatial periodic horseshoe orbits about Lagrangian points in the framework of restricted three-body problem with radiation pressure and albedo as perturbations. The global grid search technique for obtaining both types of periodic horseshoe orbits is described. Further, several families of horseshoe orbits are obtained and then the orbital behaviour of each periodic orbit is investigated. By global grid search method, spatial axi-symmetric horseshoe orbits and their families are obtained via pseudo-arclength continuation. Interestingly, new forms of spatial horseshoe orbits are constructed and their orbital properties are analysed. Moreover, it is found that stable horseshoe orbits exists for different range of x0 in planar as well as in spatial case. Using parameter continuation, the effect of radiation pressure and albedo are discussed for the evolution of horseshoe orbits and found that the radiation pressure affects the shape of horseshoe orbits more then that of albedo. These results are helpful to analyse more generalized problem with other perturbations.

Simulations of energetic alpha particle loss in the presence of toroidal field ripple in the CFETR tokamak

Energetic alpha particle losses with the toroidal field ripple and the Coulomb collision in the CFETR tokamak have been simulated by using the orbit-following code GYCAVA for the steady-state and hybrid scenarios. The effects of the outer boundary and the ripple amplitude on alpha particle losses have been investigated. The loss fractions and heat loads of alpha particles in the hybrid scenario are much smaller than those in the steady-state scenario for a significant ripple amplitude. Some alpha particles in the plasma core are lost due to the ripple stochastic transport for a large ripple amplitude parameter. The heat loads with the last closed flux surface boundary are different from those with the wall boundary for the CFETR tokamak, which can be explained by typical alpha particle orbits. Discrete heat load spots have been observed in alpha particle loss simulations, which is due to the ripple well loss. The transition of the lost alpha particle behavior from the ripple stochastic diffusion to the ripple well trapping has been identified in our CFETR simulations. The Coulomb collision effect is responsible for this transition.

Reconstructing the orbit type stratification of a torus action from its equivariant cohomology

We investigate what information on the orbit type stratification of a torus action on a compact space is contained in its rational equivariant cohomology algebra. Regarding the (labelled) poset structure of the stratification, we show that equivariant cohomology encodes the subposet of ramified elements. For equivariantly formal actions, we also examine what cohomological information of the stratification is encoded. In the smooth setting, we show that under certain conditions—which in particular hold for a compact orientable manifold with discrete fixed point set—the equivariant cohomologies of the strata are encoded in the equivariant cohomology of the manifold.

Orbit classification in the restricted three-body problem with the effect of three-body interaction

The modified circular restricted three-body problem is numerically investigated to classify the orbits of the test particle. We perform a numerical analysis on the various two-dimensional plane, i.e., (x,C)-plane, (y,C)-plane, and (x,y)-plane to classify the initial conditions on the these planes and distinguish following four types of orbits: (i) the bounded orbits, (ii) collision with the primary m1, (iii) collision with the primary m2, and (iv) escaping orbits. The motion of the test particle are evaluated numerically, by illustrating the color-coded diagrams (CCDs), where the starting conditions are linked to the orbit type and numerically evaluated as a function of the Jacobian constant C, the initial value of the x−co-ordinate and the Jacobian constant C or the x,y−co-ordinates, or the y−co-ordinate and Jacobian constant. Moreover, in the mean time we have also noted the associated time for classifications of each of the starting conditions on the various 2D-planes.

Characterization of beam ion loss in high poloidal beta regime on EAST

A critical issue for achieving the integrated operation of steady-state long-pulse high-confinement (H-mode) plasmas on experimental advanced superconducting tokamak (EAST) is to improve beam ion population confinement during neutral beam injection (NBI). To study the characterization of beam ion loss and improve beam ion confinement, the steady-state long pulse scenario discharges were conducted on EAST (β p ⩾ 2.0, β N ⩾ 1.7, q 95 ⩾ 6.7 and H 98y2 ⩾ 1.1) with NBI heating. Based on neutron yield, the beam voltage and line-averaged electron density were adjusted from 50 kV to 60 kV and 4.4 × 1019 m−3 to 5.0 × 1019 m−3, respectively. The results show that the dominant mechanisms of beam ion loss are shine-through loss, prompt loss, and stochastic ripple loss. The shine-through loss fraction is determined by initial velocity, flight time and entire beam path. The change in prompt loss fraction is caused by the change in the deposition of beam ions. The change in stochastic ripple loss fraction is caused by the change in the initial fraction of trapped-confined ions. Detailed physics shows that the prompt loss fraction during counter-Ip injections (∼45%) is far larger than during co-Ip injections (∼5%) due to the finite orbit width. The lost ions are mainly deposited on the lower divertor or below the midplane since the direction of magnetic drift is vertical down. The orbit types of prompt loss during counter-Ip injections are mainly trapped-lost and ctr-passing lost. To minimize the prompt loss fraction during counter-Ip injections, a reversed Ip configuration (rev-Ip) discharge #94758 was conducted. The result suggests that the beam ion wall load fraction during counter-Ip tangential injection (∼3%) is far lower than that in normal Ip configuration (nor-Ip) discharge #94820. It is also found that the confinement of beam ion population in the counter-Ip injection #94758 was greatly improved when compared to #94820. This study can provide unique support for the improvement of beam ion population confinement and for the performance evaluation of the NBI system on EAST and future tokamaks.

Systematic TLE data improvement by neural network for most cataloged resident space objects

Two-line element sets (TLE) released by the 18th Space Control Squadron are the most complete source of information for space situational awareness in the public domain. They are used in a wide range of contexts that include navigation of nanosatellites and ground communication. However, the TLE data are known for having significant bias and errors. Predicting the bias of TLE can be a way to correct them automatically and hence optimize the systems that rely on them at low cost, for instance for reentry calculations and mission analysis. This paper shows the performance of a neural network trained on more than 4500 inactive resident space objects (RSO) on 10 months of orbital data, on all types of orbits. It is shown that the state vector errors are corrected by at least 40% for 70% of the TLE and that the residual error distributions are well described by a Student’s t-distribution for which covariance elements are defined consistently. The performance of the trained neural network are shown to be similar for multiple active satellites.

Selection of time-dependent worst-case thermal environmental conditions for Low Earth Orbit spacecrafts

When facing the thermal analysis of a Low Earth Orbit satellite, selecting the worst-case orbit where the minimum and maximum temperatures are reached is essential for ensuring the success of the mission. Typical orbits have a non-constant Solar Beta Angle throughout the year providing a wide range of orbits with different heat loads and eclipses. It is possible to focus the analysis on a single orbit configuration by a rough analysis using a simple model. In order to achieve this, every potential orbit with their corresponding thermal environmental parameters must be analysed based on real data. The direct solar radiation, the albedo and the Earth Outgoing Longwave Radiation (OLR) characterize the thermal environment to be taken into account. However, their values have a wide variability which depend on many parameters. Based on the characteristics of the orbit and the system thermo-optical properties and characteristic time, it is possible to obtain particularized profiles of albedo and OLR that would lead the system to its maximum and minimum temperatures. The conventional criteria, which is studied here in depth, provides two constant values of albedo and OLR as the hot and cold worst-cases. This is suitable for massive system or cases in which the characteristics times of the system are high. For lighter elements or low characteristic times, temperatures throughout the orbit deviate considerably from the real behaviour. In contrast, the methodology here proposed provides a time-dependant profile that allows for the determination of a system temperature response closer to the real one, together with the potential minimum and maximum temperatures of the orbit, in order to optimize the design and avoid the oversizing.

A medium-scale study of using machine learning fusion to improve TLE prediction precision without external information

This paper presents a machine learning (ML) approach that can improve orbit prediction precision and reduce uncertainties with a properly designed fusion strategy. The ML models are trained based on historical TLE sets and then ML-modifications are generated for the future states and uncertainty predictions. The ML-modification is first interpreted as a pseudo-measurement of the true orbit prediction error and then fused with the conventional orbital state and uncertainty propagation result. The regularized particle filter (PF) with progressive correction and systematic sampling is adopted for uncertainty propagation while using the Simplified General Perturbations #4 (SGP4) model. Comprehensive experiments are conducted and analyzed on over 100 resident space objects (RSOs) in different orbit types. The results demonstrate that the fusion strategy enables the ML approach to work with the advanced PF prediction method. The prediction precision can be significantly improved for the majority of the cases. The prediction accuracy is observed to be improved in some cases but without a clear pattern. The results and analysis also suggest that future studies of a monitoring system facilitating the fusion process would be helpful in practical applications.

Proton-Induced Activation of New Scintillator Materials: SrI, GAGG, CLLB, CLLBC, TLYC, CLYC-7

In recent years, a number of new scintillator materials with improved energy resolution for gamma-ray detectors have become commercially available for use in terrestrial-based homeland security applications, and some are being incorporated into instrumentation for space. Unlike terrestrial applications, the harsh environment of space&#x2014;in particular, energetic trapped particles, cosmic rays, and neutrons&#x2014;often activates these materials, and any improvement in sensitivity as a result of improved energy resolution could be offset by the additional background due to activation. The purpose of this work was to measure potential backgrounds due to trapped and cosmic-ray proton-induced activation in the new materials: SrI₂:Eu (SrI), ⁷Li-enriched Cs₂LiYCl₆:Ce (CLYC-7), Cs₂LiLaBr₆:Ce (CLLB), Cs₂LiLa(Br,Cl)₆:Ce (CLLBC), Tl₂LiYCl₆:Ce (TLYC), and Gd₃(Al,Ga)₅O₁₂:Ce (GAGG). Using a large-diameter 64-MeV proton beam, detectors were irradiated with a total dose of 100 rad (Si), roughly equivalent to the annual dose in a typical low earth orbit. Measurements were made with a single 100&#x0025; relative efficiency high-purity germanium (HPGe) (0.05&#x2013;3 MeV) and the irradiated detector. Two multichannel analyzers (MCAs) operating in the event mode were used to collect the data. Time-tagged events were processed into various spectral integration times for analysis, and characteristic gamma-ray energies and decay times were used to identify activation products. Most of the identified activation products were the result of (p, xn) reactions, with a few exceptions. This work identifies the primary radioisotopes generated by energetic proton activation in six different scintillator materials.

RESEARCH ON QUALITY STATUS QUO AND QUALITY EVALUATION THEORY OF NATURAL RESOURCES REMOTE SENSING DATA AND COMMON PRODUCTS

Abstract. The research on the quality evaluation of satellite remote sensing data and common products of natural resources is to analyze the role of satellite remote sensing data and common products in the management of natural resource elements such as land, forest, grassland, wetland and water, study their quality models and quality evaluation methods, build a quality evaluation index system, and study the technical processes and methods of quality inspection, So as to provide basic support for the research on the framework of quality evaluation standard system and provide technical support for promoting the application of natural resources satellite remote sensing data and common products. Firstly, this paper combs and summarizes the list of 9 categories and 32 types of natural resources satellite remote sensing data and common products. Focusing on the current situation and characteristics of the quality research of typical natural resources satellite remote sensing data and common products, this paper summarizes the quality inspection contents and evaluation methods, existing and proposed standards at home and abroad, the quality characteristics of natural resources satellite remote sensing data and common products are analysed. On this basis, a complete quality evaluation system framework of natural resources satellite remote sensing data and common products is established, and quality elements and quality sub elements are proposed to describe the quality model of natural resources satellite remote sensing data and common products, so as to form a method suitable for evaluating the quality of natural resources satellite remote sensing data and common products.

Inferring topological operations on generalized maps: Application to subdivision schemes

The design of correct topological modeling operations is known to be a time-consuming and challenging task. However, these operations are intuitively understood via simple drawings of a representative object before and after modification. We propose to infer topological modeling operations from an application example. Our algorithm exploits a compact and expressive graph-based language. In this framework, topological modeling operations on generalized maps are represented as rules from the theory of graph transformations. Most of the time, operations are generic up to a topological cell (vertex, face, volume). Thus, the rules are parameterized with orbit types indicating which kind of cell is involved. Our main idea is to infer a generic rule by folding a graph comprising a copy of the object before modification, a copy after modification, and information about the modification. We fold this graph according to the cell parametrization of the operation under design. We illustrate our approach with some subdivision schemes because their symmetry simplifies the operation inference.

Quantifying the uncertainty of lake-groundwater interaction using the forward uncertainty propagation framework: The case of Lake Urmia

The interaction between a lake and groundwater has important implications to the quantity and quality of water in both environments. Quantification of lake-groundwater interaction (LGI) has been challenging in regions with limited in-situ data. LGI can be quantified by physically-based models, direct measurement of seepage, measurements of conservative chemical or isotopic tracers, and lake water balance. Despite the accuracy of the methods based on hydrochemical or isotopic measurements and analysis, they require extensive field data that are costly to collect in large lakes. Instead, the data required to quantify LGI by the lake water budget method can be obtained via typical ground measurements and satellite remote sensing. However, the influence on the estimated LGI imposed by the uncertainty associated with the other components of lake water budget (e.g., precipitation, evaporation, and inflow/outflow) is still poorly understood. In this study, we coupled a forward uncertainty propagation framework with the lake water budget to estimate the uncertainty of LGI using Latin-Hypercube sampling. We implemented the above framework in the hypersaline Lake Urmia (LU), located in the northwestern Iran, over five consecutive study periods between September 2017 and May 2020. The results revealed the exchange of flow from groundwater to the LU in all studied periods, ranging between 0.2 million cubic meters (MCM)/day and 7.6 MCM/day. The relative contribution of LGI in the water budget varied between 3% and 37%. The results of the uncertainty analysis further demonstrated that the cumulative probability of LGI < 0, which indicates flow direction from the LU to groundwater, was insignificant in all the study periods ranging between 0.001 and 0.35.

Stochastic optimization for stationkeeping of periodic orbits using a high-order Target Point Approach

Periodic orbits in the Restricted Three-Body Problem are widely adopted as nominal trajectories by different missions. To maintain periodic orbits in a three-body regime, a stationkeeping strategy based on a high-order Target Point Approach (TPA) is proposed, where fuel-optimal and error-robust TPA parameters are acquired from stochastic global optimization. Accurate TPA maneuvers are calculated in a high-order fashion enabled by Differential Algebra techniques. Orbit determination epoch is selected using a sensitivity analysis based on the convergence radius of a stroboscopic map. Stochasticity is handled by incorporating Monte Carlo simulations in the process of optimization and the evaluation of high-order ODE expansions is employed to supplant the time-consuming numerical integration. Two specific types of periodic orbits, Near Rectilinear Halo Orbits and Quasi-Satellite Orbits, are investigated to demonstrate the validity and efficiency of the strategy.

Fast vibro-acoustic simulation methods of satellite components

PurposeThis paper aims to fast predict vibration responses of specific locations in the satellite subject to acoustic environment. It proposes a set of vibro-acoustic simulation methods of satellite components to represent their conditions in the whole satellite during the ground tests or launching. This study aims to use vibro-acoustic models of satellite components to replace that of hard modeling and time-consuming whole satellite when only local responses are concerned.Design/methodology/approachThis paper adopted experimental and numerical studies, with the latter based on the finite element (FE), statistical energy analysis (SEA) and FE-SEA hybrid theories. The vibro-acoustic model of the whole satellite was built and verified by experimental data. Based on the whole satellite model and experimental results, the fast vibro-acoustic simulation methods of all kinds of typical satellite components were discussed.FindingsThis paper shows that the models about satellite components not only show high consistency but also reduce 61.6% to 99.8% times compared with the whole satellite model. The recommended fast simulation methods for all kinds of typical satellite components were given in comprehensive consideration of the model accuracy, time required and response accessibility.Originality/valueThis paper fulfils an identified need to perform fast vibro-acoustic prediction of the local positions in satellites.