A simple and valid analysis method for orbit anomaly detection

A simple analysis method for orbit anomaly detection, called semi-major axis change method (SACM) was presented by using a relationship between the change of orbit parameters and velocity increments. In this method, the mean value and standard deviation of the semi-major axis change in different time intervals were first calculated according to historical data. Then, these two parameters, the mean value and standard deviation of the semi-major axis change, are chosen as basis variables and combined as an anomalous criterion. For orbit objects with different characteristic, anomalous thresholds were given in different time intervals for identifying the anomalies of the orbital objects. Finally, this method is used for low earth orbit (LEO) satellites and American–Russian breakup debris. By adopting this method, the characteristics of the orbit change were given. The accuracy rate of anomaly analysis for LEO satellites and American–Russian breakup debris can reach to 100%, which demonstrates that the method was rapid and valid.     

大气阻力参数修正对低轨空间目标轨道预报精度的改进

对于低轨空间目标, 大气阻力是影响轨道预报精度的主要摄动力. 本文提出了一种 基于空间环境数据和神经网络模型的空间目标大气阻力参数修正方法, 基于目 标的历史两行元根数, 通过模拟得到外推一天轨道预报中预报结果与观测数据 符合最好的阻力调制系数, 分析表明其与太阳F_10.7指数和地磁Ap指数具有很好的相关性. 根据已有数据, 构建神经网络模型, 实现对阻力调制系数 的补偿计算, 从而改进低轨目标外推一天的轨道预报. 结果表明, 神经网络模 型相比两行元根数能够更及时地对空间环境变化进行响应. 将该方案应用于天 宫一号和国际空间站的外推一天轨道预报, 验证了方案的正确性和普适性, 对 地磁扰动引起的较大预报误差改进效果更好, 误差能够降低50%~60%; 平均而言, 预报精度可以提高约30%, 改进成功率达到80%左右.      

VLBI observations to the APOD satellite

The APOD (Atmospheric density detection and Precise Orbit Determination) is the first LEO (Low Earth Orbit) satellite in orbit co-located with a dual-frequency GNSS (GPS/BD) receiver, an SLR reflector, and a VLBI X/S dual band beacon. From the overlap statistics between consecutive solution arcs and the independent validation by SLR measurements, the orbit position deviation was below 10?cm before the on-board GNSS receiver got partially operational. In this paper, the focus is on the VLBI observations to the LEO satellite from multiple geodetic VLBI radio telescopes, since this is the first implementation of a dedicated VLBI transmitter in low Earth orbit. The practical problems of tracking a fast moving spacecraft with current VLBI ground infrastructure were solved and strong interferometric fringes were obtained by cross-correlation of APOD carrier and DOR (Differential One-way Ranging) signals. The precision in X-band time delay derived from 0.1?s integration time of the correlator output is on the level of 0.1?ns. The APOD observations demonstrate encouraging prospects of co-location of multiple space geodetic techniques in space, as a first prototype.     

Estimation of ballistic coefficients of low altitude debris objects from historical two line elements

This paper presents a new method for estimating ballistic coefficients (BCs) of low perigee debris objects from their historical two line elements (TLEs). The method uses the drag perturbation equation of the semi-major axis of the orbit. For an object with perigee altitude below 700 km, the variation in the mean semi-major axis derived from the TLE is mainly caused by the atmospheric drag effect, and therefore is used as the source in the estimation of the ballistic coefficient. The method is tested using the GRACE satellites, and a number of debris objects with external ballistic coefficient values, and agreements of about 10% are achieved.     

Measuring atmospheric density using GPS–LEO tracking data

We present a method to estimate the total neutral atmospheric density from precise orbit determination of Low Earth Orbit (LEO) satellites. We derive the total atmospheric density by determining the drag force acting on the LEOs through centimeter-level reduced-dynamic precise orbit determination (POD) using onboard Global Positioning System (GPS) tracking data. The precision of the estimated drag accelerations is assessed using various metrics, including differences between estimated along-track accelerations from consecutive 30-h POD solutions which overlap by 6 h, comparison of the resulting accelerations with accelerometer measurements, and comparison against an existing atmospheric density model, DTM-2000. We apply the method to GPS tracking data from CHAMP, GRACE, SAC-C, Jason-2, TerraSAR-X and COSMIC satellites, spanning 12 years (2001–2012) and covering orbital heights from 400 km to 1300 km. Errors in the estimates, including those introduced by deficiencies in other modeled forces (such as solar radiation pressure and Earth radiation pressure), are evaluated and the signal and noise levels for each satellite are analyzed. The estimated density data from CHAMP, GRACE, SAC-C and TerraSAR-X are identified as having high signal and low noise levels. These data all have high correlations with anominal atmospheric density model and show common features in relative residuals with respect to the nominal model in related parameter space. On the contrary, the estimated density data from COSMIC and Jason-2 show errors larger than the actual signal at corresponding altitudes thus having little practical value for this study. The results demonstrate that this method is applicable to data from a variety of missions and can provide useful total neutral density measurements for atmospheric study up to altitude as high as 715 km, with precision and resolution between those derived from traditional special orbital perturbation analysis and those obtained from onboard accelerometers.     

LEO空间碎片甚短弧角度数据初轨确定方法对比

光学观测是空间目标观测中最常见的一种观测方式。采用扫描模式工作时光学观测得到的观测弧段弧长通常很短,有时甚至不到被观测空间目标运行周期的1%,这样的角度数据被称为甚短弧角度数据。基于近圆LEO空间碎片地基实测场景,研究比较仅利用角度数据进行初始轨道确定常用方法的性能差异,分析观测弧长对不同初轨确定算法的定轨成功率和误差的影响,为初轨确定工作提供参考。对比分析了常用的几种方法,包括Laplace方法、Gauss方法、Gooding方法和近几年提出的距离搜索算法等。大规模实测数据处理结果显示,距离搜索算法的成功率高于90%,初轨半长轴统计误差仅为25 km。初轨结果表明,距离搜索算法定轨成功率高于其他算法。研究成果可为解决空间碎片初轨确定问题提供参考。      

基于轨道预报的热层模式评估

在太阳活动高低年的地磁平静/扰动环境下,利用不同热层大气模式J77,DTM78,MSIS00,JB2008和CHAMP加速度计反演密度,分析有无先验信息条件下的轨道预报误差.结果表明无先验信息的精密轨道预报中,热层模式的性能可能被弹道系数等参数偏差干扰,此时预报误差不能作为模式性能的评价标准.先验信息对轨道预报精度提升非常明显,尤其是地磁扰动期先进热层模式性能得以展现,轨道预报误差为无先验信息情况下的10%～25%.目前热层模式的主要缺陷存在于地磁扰动期.各模式之间的差异是:JB2008模式可以通过线性和单一频率周期项补偿,而J77及DTM78等模式还存在更多频率的误差.本文对不同情况下精密轨道预报的研究结果可为空间碎片碰撞预警等工程实践提供参考.      

Orbit improvement for GTO objects using follow-up observations

The Astronomical Institute of the University of Bern was and is conducting several search campaigns for space debris in the geostationary ring (GEO) and the geostationary transfer orbit (GTO). First tests to build up a catalogue of satellites and space debris were performed recently. As the discovery observations of an object usually cover a time interval of a few minutes only, the first orbits determined are assumed to be circular. For GEO objects a circular orbit is a rather good approximation. This is certainly not the case for GTO objects. Nevertheless, a circular orbit seems to be an acceptable approximation for a short time interval around the observations. The first orbits can be used to acquire follow-up observations, which allow the determination of elliptical orbits. The maximum allowed time span between the detection and the follow-up for a successful recovery is found using simulated GTO orbits and observations. Further follow-up observations are simulated in order to study the orbit improvement process and the required force model. The accuracy of orbits needed to build up a catalogue is studied. The simulations are compared to the results achieved with observations acquired by the 1 m telescope on Tenerife.     

An improved focusing method for geosynchronous SAR

More and more attention is paid to Geosynchronous Orbit (GEO) Synthetic Aperture Radar (SAR) in recent years due to its fine temporal resolution and large coverage, so that GEO SAR will play an important role in monitoring natural disasters, but its imaging is more difficult compared to lower Earth orbit (LEO) SAR because of the increase of orbit height. This paper mainly studies the coverage property and focusing method in GEO SAR. As is known to us, the coverage of a GEO SAR satellite can reach 1/3 of the whole Earth, and the revisiting time can reduce to 2 h, which will remarkably improve the capability in ocean applications, earth dynamics and natural hazards management and so on. Compared with the imaging in LEO SAR, a problem in GEO SAR is that the linear trajectory model can bring a big error due to the long synthetic aperture time, so that the classical imaging algorithms in LEO SAR cannot be directly applied in GEO SAR. Using the Norm method and Taylor expansion method, this paper gains an accurate slant range model, which can resolve the big error of the linear trajectory at perigee and collapse of the linear trajectory at apogee. Furthermore, this paper deduces a novel imaging algorithm for GEO SAR by means of series reversion, which realizes the focusing on large scene under the synthetic aperture time of 100 s. Finally, the simulation results at apogee and perigee prove the correction of the slant range model and imaging algorithm.     

利用卫星两行轨道根数反演热层密度

两行轨道根数（TLEs）是基于一般摄动理论产生的用于预报地球轨道飞行器位置和速度的一组轨道参数,通过求解大气阻力微分方程,可反演出热层大气密度. 本文选取近圆轨道CHAMP卫星和椭圆轨道Explorer8卫星,以两行轨道根数数据为基础,计算反弹道系数,并根据不同轨道特征采用两种不同反演方法对热层大气密度进行研究. 结果表明,这两种方法反演得到的大气密度与实测值均符合较好,其中CHAMP卫星的反演结果和经验模式值相对于实测值的误差分别为7.94%和13.94%,Explorer8卫星的误差分别为9.04%和14.32%. 相比模式值,利用两行轨道根数数据反演的热层大气密度更接近于实测值,说明该方法可以作为获取大量可靠大气密度数据的一种有效途径.      

Storm-time atmospheric density modeling using neural networks and its application in orbit propagation

Upper atmospheric densities during geomagnetic storms are usually poorly estimated due to a lack of clear understanding of coupling mechanisms between the thermosphere and magnetosphere. Consequently, the orbit determination and propagation for low-Earth-orbit objects during geomagnetic storms have large uncertainties. Artificial neural networks are often used to identify nonlinear systems in the absence of rigorous theory. In the present study, an attempt has been made to model the storm-time atmospheric density using neural networks. Considering the debate over the representative of geomagnetic storm effect, i.e. the geomagnetic indices ap and Dst, three neural network models (NNM) are developed with ap, Dst and a combination of ap and Dst respectively. The density data used for training the NNMs are derived from the measurements of the satellites CHAMP and GRACE. The NNMs are evaluated by looking at: (a) the mean residuals and the standard deviations with respect to the density data that are not used in training process, and (b) the accuracy of reconstructing the orbits of selected objects during storms employing each model. This empirical modeling technique and the comparisons with the models NRLMSIS-00 and Jacchia-Bowman 2008 reveal (1) the capability of neural networks to model the relationship between solar and geomagnetic activities, and density variations; and (2) the merits and demerits of ap and Dst when it comes to characterizing density variations during storms.     

On the usefulness of atmospheric and oceanic angular momentum in recovering polar motion and gravity field variations in a unified process

Earth rotation parameters (ERPs) are excited by variations in the mass distribution on the Earth’s surface and the exchange of angular momentum between the atmosphere and oceans and the solid Earth. The same mass redistribution causes temporal changes in the gravity field coefficients with the second degree harmonics related to the rotational deformation and hence to changes in the Earth’s inertial tensor. If precise models of the atmospheric and oceanic angular momentum (AM) are available solution for polar motion and degree 2 Stokes harmonics can be unified. In this study we utilize SLR tracking of LAGEOS to compare (i) degree 2 harmonics from ERPs and gravitation, and (ii) LAGEOS excitation functions and geophysical data (mass + motion). Finally, we investigate to what extent a unified approach is possible with current models for AM data and gravity mass change estimated from ERP within orbit determinations.     

AIUB-CHAMP02S: The influence of GNSS model changes on gravity field recovery using spaceborne GPS

The gravity field model AIUB-CHAMP02S, which is based on six years of CHAMP GPS data, is presented here. The gravity field parameters were derived using a two step procedure: In a first step a kinematic trajectory of a low Earth orbiting (LEO) satellite is computed using the GPS data from the on-board receiver. In this step the orbits and clock corrections of the GPS satellites as well as the Earth rotation parameters (ERPs) are introduced as known. In the second step this kinematic orbit is represented by a gravitational force model and orbit parameters.     

MULPEX: A compact multi-layered polymer foil collector for micrometeoroids and orbital debris

Detailed studies of preserved hypervelocity impact residues on spacecraft multi-layer insulation foils have yielded important information about the flux of small particles from different sources in low-Earth orbit (LEO). We have extended our earlier research on impacts occurring in LEO to design and testing of a compact capture device. MUlti-Layer Polymer EXperiment (MULPEX) is simple, cheap to build, lightweight, of no power demand, easy to deploy, and optimised for the efficient collection of impact residue for analysis on return to Earth. The capture medium is a stack of very thin (8 and 40 μm) polyimide foils, supported on poly-tetrafluoroethylene sheet frames, surrounded by a protective aluminium casing. The uppermost foil has a very thin metallic coating for thermal protection and resistance to atomic oxygen and ultra-violet exposure. The casing provides a simple detachable interface for deployment on the spacecraft, facing into the desired direction for particle collection. On return to the laboratory, the stacked foils are separated for examination in a variable pressure scanning electron microscope, without need for surface coating. Analysis of impact residue is performed using energy dispersive X-ray spectrometers. Our laboratory experiments, utilising buck-shot firings of analogues to micrometeoroids (35–38 μm olivine) and space debris (4 μm alumina and 1 mm stainless steel) in a light gas gun, have shown that impact residue is abundant within the foil layers, and preserves a record of the impacting particle, whether of micrometer or millimetre dimensions. Penetrations of the top foil are easily recognised, and act as a proxy for dimensions of the penetrating particle. Impact may cause disruption and melting, but some residue retains sufficient crystallographic structure to show clear Raman lines, diagnostic of the original mineral.     

Improved kHz-SLR tracking techniques and orbit quality analysis for LEO missions

Satellite gravity field missions such as CHAMP, GRACE and GOCE are designed as low Earth orbiting spacecraft (LEO) with orbit heights of about 250–500 km. The challenging mission objectives require a very precise knowledge of the satellite orbit position in space. For these missions precise orbit information is typically provided by GPS satellite-to-satellite tracking (SST) observations supported by satellite laser ranging (SLR).     

Onboard orbit determination using GPS observations based on the unscented Kalman filter

Spaceborne GPS receivers are used for real-time navigation by most low Earth orbit (LEO) satellites. In general, the position and velocity accuracy of GPS navigation solutions without a dynamic filter are 25 m (1σ) and 0.5 m/s (1σ), respectively. However, GPS navigation solutions, which consist of position, velocity, and GPS receiver clock bias, have many abnormal excursions from the normal error range for space operation. These excursions lessen the accuracy of attitude control and onboard time synchronization. In this research, a new onboard orbit determination algorithm designed with the unscented Kalman filter (UKF) was developed to improve the performance. Because the UKF is able to obtain the posterior mean and covariance accurately by using the second-order Taylor series expansion through the sampled sigma points that are propagated by using the true nonlinear system, its performance can be better than that of the extended Kalman filter (EKF), which uses the linearized state transition matrix to predict the covariance. The dynamic models for orbit propagation applied perturbations due to the 40 × 40 geo-potential, the gravity of the Sun and Moon, solar radiation pressure, and atmospheric drag. The 7(8)th-order Runge–Kutta numerical integration was applied for orbit propagation. Two types of observations, navigation solutions and C/A code pseudorange, can be used at the user’s discretion. The performances of the onboard orbit determination were verified using real GPS data of the CHAMP and KOMPSAT-2 satellites. The results of the orbit determination were compared with the precision orbit ephemeris (POE) of the CHAMP and KOMPSAT-2 satellites.     

Instability of the present LEO satellite populations

Several studies conducted during 1991–2001 demonstrated, with some assumed launch rates, the future unintended growth potential of the Earth satellite population, resulting from random, accidental collisions among resident space objects. In some low Earth orbit (LEO) altitude regimes where the number density of satellites is above a critical spatial density, the production rate of new breakup debris due to collisions would exceed the loss of objects due to orbital decay.     

利用大气阻力的横向编队维持控制

研究了航天器在近圆轨道面内横向固定间隔距离内伴飞编队维持问题。基于经典轨道要素偏差法分析了相对运动特性和大气阻力对相对运动的影响。根据利用大气阻力引起的横向相对运动漂移,设计了有利于长期伴飞编队维持的初始半长轴偏差和伴飞边界点的期望半长轴偏差,进一步给出了进行伴飞维持的边界点横向速度脉冲。仿真结果表明,该控制策略进行伴飞编队维持是可行的,维持所需的速度脉冲次数少、速度增量小,且算法简单,有利于航天器自主化实现。     

Global MGS TES data and Mars-GRAM validation

Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many Mars mission applications. From 0 to 80 km, it is based on NASA Ames Mars General Circulation Model (MGCM), while above 80 km it is based on University of Michigan Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topography from Mars Global Surveyor Mars Orbiter Laser Altimeter (MOLA). Validation studies are described comparing Mars-GRAM with a global summary data set of Mars Global Surveyor Thermal Emission Spectrometer (TES) data. TES averages and standard deviations were assembled from binned TES data which covered surface to ∼40 km, over more than a full Mars year (February 1999–June 2001, just before start of a Mars global dust storm). TES data were binned in 10° × 10° latitude–longitude bins (36 longitude bins, centered at 5°–355°, by 18 latitude bins, centered at −85° to +85°), and 12 seasonal bins (based on 30° increments of L_s angle). Bin averages and standard deviations were assembled at 23 data levels (temperature at 21 pressure levels, plus surface temperature and surface pressure). Two time-of-day bins were used: local time near 2 or 14 h. Two dust optical depth bins were used: infrared optical depth, either less than or greater than 0.25 (which corresponds to visible optical depth less than or greater than about 0.5). For interests in aerocapture and precision entry and landing, comparisons focused on atmospheric density. TES densities versus height were computed from TES temperature versus pressure, using assumptions of perfect gas law and hydrostatics. Mars-GRAM validation studies used density ratio (TES/Mars-GRAM) evaluated at data bin center points in space and time. Observed average TES/Mars-GRAM density ratios were generally 1 ± 0.05, except at high altitudes (15–30 km, depending on season) and high latitudes (>45°N), or at most altitudes in the southern hemisphere at L_s ∼ 90° and 180°. Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of ∼2.5% for all data, or ∼1–4%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 h and 7.1% for local time 14 h. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about three times the standard deviation of TES data about the TES mean value at a given position and season.     

Autonomous broadcast ephemeris improvement for GNSS using inter-satellite ranging measurements

This paper discusses the concept of using inter-satellite ranging (ISR) measurements of the satellites of a Global Navigation Satellite System (GNSS) for autonomous broadcast ephemeris improvement. Firstly the inter-satellite ranging is modeled to obtain the clock and orbit error observables. The orbit error observable is analyzed and its observation equation is provided. Both least-squares estimation and Kalman Filter approach are proposed to estimate satellite clock errors, while solely the Kalman Filter is used to estimate the orbit errors. All these algorithms are validated using true broadcast ephemeris and precise ephemeris of GPS along with the simulated ranging noise. Based on the settings adopted in the test, the result shows that the orbit accuracy of the precise ephemeris using the proposed method is around 20–50 cm and the accuracy of the satellite clock can reach 20 cm while ranging noise is assumed to be 0.45 m (1σ). The User Ranging Error (URE) is improved from 1.05 m to 0.34 m, which is comparable to other sources of precise ephemeris or even better, while the proposed approach has many advantages such as compatibility and accessibility. It is also noted that the proposed method may provide useful functions in determining inter-constellation coordinate and time differences autonomously for better interoperability and interchangeability in the multi GNSS operation era.