DISCOS - ESA''s database and information system characterising objects in space

This paper presents an overview of the main features of ESA's future space debris database DISCOS (Database and Information System Characterising Objects in Space). The DISCOS system has been developed around an ORACLE relational database management software by the University of Kent (UK) under an ESA contract. The DISCOS catalogue will be installed at ESOC, the European Space Operations Centre, and serve as a common ESA information system for the space debris environment.     

一种全球临近空间大气密度建模方法及应用

基于TIMED/SABER卫星2002—2018年观测的20~100 km大气密度数据,统计获得多年月平均值和标准偏差的全球网格数据。利用网格数据,分析了大气密度的变化特征。以网格数据为基准,计算了USSA76的相对偏差,分析了USSA76相对偏差的分布特征。以网格数据为驱动,将大气密度表征为平均值与大尺度扰动量和小尺度扰动量的加和,大尺度扰动和小尺度扰动分别采用余弦函数和一阶自回归模型表征,初步建立了全球临近空间大气密度模型。通过对比模型仿真值与激光雷达观测值,表明模型仿真值与观测值具有较好的吻合度,验证了建模方法的可行性。利用蒙特卡罗方法可再现给定轨迹上所有可能的大气状态。      

临近空间大气密度扰动对高超声速飞行器气动热环境的影响

基于TIMED/SABER 2002—2018年大气密度观测数据,统计分析了20~80 km大气密度扰动对高超声速飞行器飞行热环境的影响。根据驻点热流估算方法给出的大气密度变化量与热流变化量之间的关系,定性和定量分析了不同月份大气密度相对变化量引起的热流变化量在垂直和水平方向的分布特征。研究表明:SABER大气密度月年均值计算的热流相对USSA76在夏季半球中高纬度地区偏高,在冬季半球偏低。在夏季半球高纬度地区约80 km附近存在热流增量的极大值,南半球夏季的极大值高于北半球夏季,尤其在南半球1月份,热流偏高可达32.2%。在经度方向,热流分布在夏季半球差异较小,冬季半球差异较大;考虑真实大气中存在的扰动时,在南半球和北半球夏季80 km附近,SABER大气密度预测的热流分别比USSA76偏高可达40.7%和36.6%。在经度方向,大气扰动引起的热流经向分布差异显著。在飞行器设计时,大气扰动的影响不能忽略;高超声速飞行器飞行应避免在夏季穿越南半球和北半球,规避热流增加带来的风险。      

Advanced ensemble modeling method for space object state prediction accounting for uncertainty in atmospheric density

For objects in the low Earth orbit region, uncertainty in atmospheric density estimation is an important source of orbit prediction error, which is critical for space traffic management activities such as the satellite conjunction analysis. This paper investigates the evolution of orbit error distribution in the presence of atmospheric density uncertainties, which are modeled using probabilistic machine learning techniques. The recently proposed “HASDM-ML,” “CHAMP-ML,” and “MSIS-UQ” machine learning models for density estimation (Licata and Mehta, 2022b; Licata et al., 2022b) are used in this work. The investigation is convoluted because of the spatial and temporal correlation of the atmospheric density values. We develop several Monte Carlo methods, each capturing a different spatiotemporal density correlation, to study the effects of density uncertainty on orbit uncertainty propagation. However, Monte Carlo analysis is computationally expensive, so a faster method based on the Kalman filtering technique for orbit uncertainty propagation is also explored. It is difficult to translate the uncertainty in atmospheric density to the uncertainty in orbital states under a standard extended Kalman filter or unscented Kalman filter framework. This work uses the so-called “consider covariance sigma point (CCSP)” filter that can account for the density uncertainties during orbit propagation. As a test-bed for validation purposes, a comparison between CCSP and Monte Carlo methods of orbit uncertainty propagation is carried out. Finally, using the HASDM-ML, CHAMP-ML, and MSIS-UQ density models, we propose an ensemble approach for orbit uncertainty quantification for four different space weather conditions.     

Accurate estimation of relative atmospheric density error on the example of uncertain geomagnetic activity information

Errors in neutral atmospheric density are the dominant contributor to unrealistic orbital state-vector covariances in low Earth orbits (LEO). Density uncertainty is caused by model-uncertainty at spatial scales below and within the model resolution, as well as input-uncertainty of the environmental parameters supplied to the semi-empirical atmospheric model.The paper at hand provides multiple contributions. First, analytic equations are derived to estimate the relative density error due to an input parameter uncertainty in any of the environmental parameters supplied to the model. Second, it is shown on the example of uncertain geomagnetic activity information, how to compute the required inputs to facilitate the accurate estimation of the relative density error.A clamped cubic splining approach for the conversion from geomagnetic amplitude (ap) to the kp index is postulated to perform this uncertainty propagation, as other algorithms were found unsuitable for this task. Results of numerical simulations with three popular semi-empirical models are provided to validate the set of derived equations. It is found that geomagnetic input uncertainty is especially important to consider in case of low global geomagnetic activity. The findings seamlessly integrate with prior work by the authors to perform density-uncertainty considering orbit estimation.     

Evaluation of recent atmospheric density models

Precision radar tracking data taken in 1985 on two spherical satellites has been used to evaluate atmospheric density models: Jacchia 1971 [CIRA 1972], Jacchia 1977, and MSIS 1983, using Cook's definition of Cd /2/. The satellites have perigee heights of 270 km and 780 km. For each day, using numerical integration, an independent trajectory was computed, including a drag scale factor (S). The difference of S from unity represents the error in the atmospheric model used to compute the drag. At 270 km the three models performed equally well, as S was consistently close to unity. This was true for all hour angles and latitudes. At 780 km the scale factors ranged from 0.1 to 1.8 for all models. However, for the Jacchia 1977 model, the average scale factor was 0.943, and represents the best model at that altitude. Computer timing was also done. For orbit computation, drag models need further improvement, and the Jacchia 1977 model seems the best available today in terms of accuracy and computational efficiency.     

Zodiacal light and space observation of faint objects

Zodiacal light is examined as a “foreground noise” limiting the space photometry of faint objects. Emphasis is given to the ways of increasing the signal to noise ratio by an appropriate choice of observational epoch. In the case of the Space Telescope, predictions of average values of this ratio for the extreme faintness case V = 28 are derived from the expected performances announced by NASA and from the recent table of zodiacal brightnesses, as obtained from observations at Tenerife ([1], table 2).     

MCMC-Particle-based group tracking of space objects within Bayesian framework

With the intense increase in space objects, especially space debris, it is necessary to efficiently track and catalog the extensive dense clusters of space objects. As the main instrument for low earth orbit (LEO) space surveillance, ground-based radar system is usually limited by its resolution while tracking small space debris with high density. Thus, the obtained measurement information could have been seriously missed, which makes the traditional tracking method inefficient. To address this issue, we conceived the concept of group tracking. For group tracking, the overall tendency of the group objects is expected to be revealed, and the trajectories of individual objects are simultaneously reconstructed explicitly. According to model the interaction between the group center and individual trajectories using the Markov random field (MRF) within Bayesian framework, the objects’ number and individual trajectory can be estimated more accurately in the condition of high miss alarm probability. The Markov chain Monte Carlo (MCMC)-Particle algorithm was utilized for solving the Bayesian integral problem. Furthermore, we introduced the mechanism for describing the behaviors of groups merging and splitting, which can expand the single group tracking algorithm to track variable multiple groups. Finally, simulation of the group tracking of space objects was carried out to validate the efficiency of the proposed method.     

Quantitative determination of the outgassing water vapor concentrations surrounding space vehicles from ion mass spectrometer measurements

Outgassing from materials as well as deliberate gaseous and liquid releases create contaminant clouds around spacecraft that can degrade both instrumentation and measurements. This paper describes a new method for estimating outgassing water vapor concentrations around space vehicles. Water vapor ions measured in the course of a rocket experiment performed at Eglin AFB, Florida, on December 12, 1980 at 2311 UT are utilized to demonstrate the technique. The H₂O concentration near the payload's surface is calculated using the rate coefficient for the fast charge transfer process, O⁺ + H₂O + H₂O⁺ + O, the source of the observed water vapor ions. It is found that the measured H₂O⁺ ions were produced within 3–4 cm of the sampling plate's surface and that the average H₂O pressure over this distance was relatively constant on ascent at 8 × 10^?6 torr, within a factor two, implying a steady outgassing rate.     

Disturbance observer based model predictive control for accurate atmospheric entry of spacecraft

Facing the complex aerodynamic environment of Mars atmosphere, a composite atmospheric entry trajectory tracking strategy is investigated in this paper. External disturbances, initial states uncertainties and aerodynamic parameters uncertainties are the main problems. The composite strategy is designed to solve these problems and improve the accuracy of Mars atmospheric entry. This strategy includes a model predictive control for optimized trajectory tracking performance, as well as a disturbance observer based feedforward compensation for external disturbances and uncertainties attenuation. 500-run Monte Carlo simulations show that the proposed composite control scheme achieves more precise Mars atmospheric entry (3.8?km parachute deployment point distribution error) than the baseline control scheme (8.4?km) and integral control scheme (5.8?km).     

Identification of uncatalogued LEO space objects by a ground-based EO array

A ground-based electro-optical (EO) array, deployed at the Jilin Space Tracking Base of Changchun Observatory, China, has been in operation since April 2017. The array has 8 small telescopes, each has an aperture of 15 cm and a field of view of 14° × 14°. On average, the array can collect angles data over 3–4 thousand Very Short Arcs (VSAs) of Low Earth Orbit (LEO) space objects each night. Correlation of the VSA angles data with the NORAD catalogue objects results in about 85% of all the VSAs being correlated to NORAD objects. The remaining 15% VSAs angles data could be supposed from uncatalogued objects. The Initial Orbit Determination (IOD) solutions of the VSAs with the range-search method and the association results of the IODs with the geometrical method are presented. The mean IOD success rate is about 91% and the True Positive (TP) rate is more than 86%. In addition, the classical Gauss, Laplace, Gooding and Double-r angles-only IOD methods are applied to process VSA angles data and their performance is assessed. The CBTA method is used to associate the IOD tracks and compared with the geometrical method. A set of procedures for identifying the uncatalogued objects based on the VSA angles data is designed. Processing of the VSA angles data from Aug 4 to Sep 30, 2017 reveals there are possibly 415 uncatalogued LEO objects.     

Track detection of high-velocity resident space objects in Low Earth Orbit

The world’s economy has become heavily dependent on the services provided by satellites. With the exponential increase in satellite launches, the population of defunct or inactive hardware in space has grown substantially. This is especially true in sensitive orbits such as the Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) regimes. These objects, collectively known as orbital debris, can reach speeds of up to 28 000km h^?1 in LEO. At these orbital speeds, even the smallest of objects can pose a considerable threat to operational satellites or astronauts. This makes the monitoring, and detection, of these objects of the utmost importance. This work describes the latest detection strategy used in one of Europe’s largest Space Situational Awareness (SSA) installation; the BIstatic RAdar for LEo Survey (BIRALES) space debris radar. We present a novel bottom-up approach that makes use of single-linkage clustering to identify faint radar streaks in spectrogram data. Tests on synthetic data have shown that the detection strategy presented in this study obtains a higher detection rate when it is compared against existing methods. Unlike other approaches, this detection strategy, using the Multi-beam streak detection strategy (MSDS) algorithm, was still able to recall 90% of the track information at an Signal-to-Noise Ratio (SNR) of 2dB.     

Impact of ITRS 2014 realizations on altimeter satellite precise orbit determination

This paper evaluates orbit accuracy and systematic error for altimeter satellite precise orbit determination on TOPEX, Jason-1, Jason-2 and Jason-3 by comparing the use of four SLR/DORIS station complements from the International Terrestrial Reference System (ITRS) 2014 realizations with those based on ITRF2008. The new Terrestrial Reference Frame 2014 (TRF2014) station complements include ITRS realizations from the Institut National de l’Information Géographique et Forestière (IGN) ITRF2014, the Jet Propulsion Laboratory (JPL) JTRF2014, the Deutsche Geodätisches Forschungsinstitut (DGFI) DTRF2014, and the DORIS extension to ITRF2014 for Precise Orbit Determination, DPOD2014. The largest source of error stems from ITRF2008 station position extrapolation past the 2009 solution end time. The TRF2014 SLR/DORIS complement impact on the ITRF2008 orbit is only 1–2 mm RMS radial difference between 1992–2009, and increases after 2009, up to 5 mm RMS radial difference in 2016. Residual analysis shows that station position extrapolation error past the solution span becomes evident even after two years, and will contribute to about 3–4 mm radial orbit error after seven years. Crossover data show the DTRF2014 orbits are the most accurate for the TOPEX and Jason-2 test periods, and the JTRF2014 orbits for the Jason-1 period. However for the 2016 Jason-3 test period only the DPOD2014-based orbits show a strong and statistically significant margin of improvement. The positive results with DTRF2014 suggest the new approach to correct station positions or normal equations for non-tidal loading before combination is beneficial. We did not find any compelling POD advantage in using non-linear over linear station velocity models in our SLR & DORIS orbit tests on the Jason satellites. The JTRF2014 proof-of-concept ITRS realization demonstrates the need for improved SLR+DORIS orbit centering when compared to the Ries (2013) CM annual model. Orbit centering error is seen as an annual radial signal of 0.4 mm amplitude with the CM model. The unmodeled CM signals show roughly a 1.8 mm peak-to-peak annual variation in the orbit radial component. We find the TRF network stability pertinent to POD can be defined only by examination of the orbit-specific tracking network time series. Drift stability between the ITRF2008 and the other TRF2014-based orbits is very high, the relative mean radial drift error over water is no larger than 0.04 mm/year over 1993–2015. Analyses also show TRF induced orbit error meets current altimeter rate accuracy goals for global and regional sea level estimation.     

超低轨道热层大气密度原位探测

超低轨道(VLEO)由于其轨道较低,在该轨道运行的航天器在对地观测、科学研究方面具有独特优势,但对该轨道的大气密度变化特性认知不足。在阐述国内外超低轨道大气密度原位探测发展历史及现状的基础上,总结了现有超低轨道大气密度原位探测技术,对中国超低轨道大气密度原位结果进行了初步分析和讨论。结果表明：在2020年10月空间环境平静期,250 km和350 km高度大气密度相差一个量级;升降轨期间,超低轨道大气密度每千米分别下降0.025×10^-12 kg/m³和0.041×10^-12 kg/m³,均小于模式值的0.5倍;北纬40°时,处于午夜的升轨段(约250 km)大气密度是处于正午的降轨段(约420 km)大气密度的11.2倍,高度的影响大于地方时的影响;不同纬度下,实测日均值和模式日均值的比值从高纬的0.49降为低纬的0.39,模式值偏大。在超低轨道上,实测值总体上比模式值小,可为大气物理研究和应用研究提供基础数据。     

编队星座相对位置精确测定与自主定轨方法

针对编队飞行星座,提出了一种全自主的高精度定轨与相对位置精确测定方法,对其主要关键技术之一的空间绝对定向的基本方案及其可行性和指标进行了研究,并进行了仿真验证.结果表明,通过编队星座星间高精度的距离测量和绝对定向观测,可以实现无需地面测控站和卫星导航系统支持下的编队星座全自主导航方案;在一定测距和测向误差条件下,绝对定轨精度可以优于20m,相对位置确定精度可优于10cm.相对误差与采样间隔有较明显关系,未来可考虑采样间隔控制在10s以内即可;绝对位置误差大小与采样间隔无明显关系,其中的主要误差是星座的整体平移误差.仿真结果验证了所提方案的正确性.      

Towards a scientific understanding of the risk from extreme space weather

Like all natural hazards, space weather exhibits occasional extreme events over timescales of decades to centuries. Historical events provoked much interest, and sometimes alarm, because bright aurora becomes visible at mid-latitudes. However, they had little economic impact because the major technologies of those eras were not sensitive to space weather. This is no longer true. The widespread adoption of advanced technological infrastructures over the past 40 years has created significant sensitivity. So these events now have the potential to disrupt those infrastructures – and thus have profound economic and societal impact. However, like all extreme hazards, such events are rare, so we have limited data on which to build our understanding of the events. This limitation is uniquely serious for space weather since it is a global phenomenon. Many other natural hazards (e.g. flash floods) are highly localised, so statistically significant datasets can be assembled by combining data from independent instances of the hazard recorded over a few decades. Such datasets are the foundation on which reliable risk assessment methodologies are built. But we have a single instance of space weather so we would have to make observations for many centuries in order to build a statistically significant dataset. We show that it is not practicable to assess the risk from extreme events using simple statistical methods. Instead we must exploit our knowledge of solar-terrestrial physics to find other ways to assess these risks. We discuss three alternative approaches: (a) use of proxy data, (b) studies of other solar systems, and (c) use of physics-based modelling. We note that the proxy data approach is already well-established as a technique for assessing the long-term risk from radiation storms, but does not yet provide any means to assess the risk from severe geomagnetic storms. This latter risk is more suited to the other approaches, but significant research is needed to make progress. We need to develop and expand techniques to monitoring key space weather features in other solar systems (stellar flares, radio emissions from planetary aurorae). And to make progress in modelling severe space weather, we need to focus on the physics that controls severe geomagnetic storms, e.g. how can dayside and tail reconnection be modulated to expand the region of open flux to envelop mid-latitudes?     

基于自适应LMS算法的空间光束快速精扫描跟踪控制方法

针对空间精密光学领域与国防应用对高精度快速光束控制的需求,给出自适应最小均方(LMS)算法对压电快摆镜进行光束扫描跟踪控制.首先描述了自适应LMS控制算法及快摆镜模型辨识方法,随后仿真分析了不同频率及迭代步长对自适应LMS算法跟踪控制的影响,最后采用自适应LMS算法进行了压电快摆镜辨识及扫描跟踪控制实验.实验结果表明,...     

A deformation model of flexible,HAMR objects for accurate propagation under perturbations and the self-shadowing effects

A new type of space debris in near geosynchronous orbit (GEO) was recently discovered and later identified as exhibiting unique characteristics associated with high area-to-mass ratio (HAMR) objects, such as high rotation rates and high reflection properties. Observations have shown that this debris type is very sensitive to environmental disturbances, particularly solar radiation pressure, due to the fact that its motion depends on the actual effective area, orientation of that effective area, reflection properties and the area-to-mass ratio of the object is not stable over time. Previous investigations have modelled this type of debris as rigid bodies (constant area-to-mass ratios) or discrete deformed body; however, these simplifications will lead to inaccurate long term orbital predictions. This paper proposes a simple yet reliable model of a thin, deformable membrane based on multibody dynamics. The membrane is modelled as a series of flat plates, connected through joints, representing the flexibility of the membrane itself. The mass of the membrane, albeit low, is taken into account through lump masses at the joints. The attitude and orbital motion of this flexible membrane model is then propagated near GEO to predict its orbital evolution under the perturbations of solar radiation pressure, Earth’s gravity field (J₂), third body gravitational fields (the Sun and Moon) and self-shadowing. These results are then compared to those obtained for two rigid body models (cannonball and flat rigid plate). In addition, Monte Carlo simulations of the flexible model by varying initial attitude and deformation angle (different shape) are investigated and compared with the two rigid models (cannonball and flat rigid plate) over a period of 100?days. The numerical results demonstrate that cannonball and rigid flat plate are not appropriate to capture the true dynamical evolution of these objects, at the cost of increased computational time.