基于修正线性组合模型的原子钟钟差预报

原子钟钟差预报在时频工作中起着重要作用.目前常用的预报模型各有优缺点,为了综合各种预报模型特点,可以考虑组合这些模型预报的结果.针对线性组合模型预报钟差时存在的问题,提出了学习权的概念,以有效地利用各种精度信息,建立了修正组合预报模型.为了验证该方法的有效性,选取了4颗GPS卫星IGS(International GN...     

Application of Grey-autoregressive Dynamic Model to Calculation of Atomic Time Scale

Because of the effects of various kinds of noises and other factors, the state of running of an atomic clock is quite complicated. In order to precisely predict the exact variation in frequency or clock rate of the atomic clock, it is necessary to study and make a reliable prediction model and via the model the clock rate of the atomic clock is predicted so as to be adopted in the monitoring of the coordinated local time and the calculation of the local atomic time. The problem how to utilize the grey model and autoregressive model to predict the clock rate of the atomic clock is discussed. The synthesized model of the two models is proposed and researched. It is tested and verified in combination with the actual data of the atomic clocks at National Time Service Center, and the computational methods of predicting the accuracies of the models corresponding to different atomic clocks are given.     

北斗系统测站钟差短期预报模型比较及其在单星定轨中的应用

北斗卫星导航系统(BDS)地面跟踪站都配置有高精度的氢原子钟,并基于精密定轨数据处理与主站的时间基准进行同步.在卫星轨道机动以及机动恢复期间,通常采用几何法定轨以及单星定轨确定卫星的轨道.而在这两种定轨模式中,需要提供精确的测站钟差作为输入.为提高定轨的实时性,需要对测站钟差进行预报处理.分析了2次多项式模型、附加周期项模型、灰色模型3种模型对北斗地面跟踪站钟差短期拟合和预报的性能,并将钟差预报结果应用于单星定轨,同时还分析了不同预报钟差用于定轨的精度.试验发现,以上3种模型对6个测站钟差的平均拟合精度分别为0.14 ns、0.05 ns、0.27 ns,预报1 h的平均精度分别为1.17 ns、0.88 ns、1.28 ns,预报2 h的平均精度分别为2.72 ns、2.09 ns、2.53 ns.采用3种模型对测站钟差进行预报并用于单星定轨,采用附加周期项的钟差预报模型轨道3维误差最小,不同模型轨道径向精度差异在3 cm以内.以上结果表明,附加周期项的站钟拟合及预报模型在北斗系统机动期间的轨道恢复数据处理具有最好的效果.     

An Improved Grey Model and Its Application Research on the Prediction of Real-time GPS Satellite Clock Errors

In the work on the real-time GPS precise point positioning, the realtime and reliable prediction of the satellite clock error is one of the keys to the realization of the GPS real-time high accuracy point positioning. The satelliteborne GPS atomic clock has high frequency, is very sensitive and extremely easy to be influenced by the outside world and its own factors. Therefore, it is very difficult for one to know well its complicated and detailed law of change, with these attributes being in accordance with the characteristics of the theory of grey system. Thus, it is considered that the process of variation of the clock error is regarded as a grey system. On the basis of the exploration of the limitations of the quadratic polynomial and grey model satellite clock error predictions, the research on the real-time prediction of the GPS satellite clock error by taking advantage of the improved grey model is proposed. Finally, the materials of the GPS satellite clock error of 3 different time intervals are used to make the accuracy analysis of the clock error prediction of different sampling intervals, to study the relation between the grey model exponential coefficient and the prediction accuracy and to make the analysis of the comparison of the prediction accuracy with that of the quadratic polynomial method. The general relation between the different types of satellite clock errors and the model exponential coefficients is summarized and compared with the IGS final clock error ephemeris product to test and verify the feasibility and availability of the improved prediction model proposed in the present article so as to provide the higher-accuracy satellite clock error products for the real-time GPS dynamic precise point positioning.     

遗传算法优化的BP神经网络卫星钟差预报

针对BP (Back Propagation)神经网络模型预测卫星钟差中权值和阈值的最优化问题, 提出了基于遗传算法优化的BP神经网络卫星钟差短期预报模型, 给出了遗传算法优化BP神经网络的基本思想、具体方法和实施步骤. 为验证该优化模型的有效性和可行性, 利用北斗卫星导航系统(BeiDou navigation satellite system, BDS)卫星钟差数据进行钟差预报精度分析, 并将其与灰色模型(GM(1,1))和BP神经网络模型预报的结果比较分析. 结果表明: 该模型在短期钟差预报中具有较好的精度, 优于GM(1,1)模型和BP神经网络模型.     

Long-term Clock Bias Prediction Based on An ARMA Model

The long-term and reliable prediction of satellite clock bias (SCB) is an important prerequisite for realizing the satellite autonomous navigation and orbit determination. Considering the shortcomings of the quadratic polynomial model (PM) and gray system model (GM) in the long-term prediction of SCB, a new prediction method of SCB based on an ARMA (Auto-Regressive Moving Average) model is proposed to represent the variation characteristics of SCB more accurately. In this paper, a careful precision analysis of the 90-day SCB prediction is made to verify the feasibility and validity of this proposed method by using the IGS (International GNSS Service) clock data. According to the variation characteristics of each satellite clock, the pattern recognition, modeling and prediction of SCB are conducted, and the detailed comparison is made with the other three models at the same time. The results show that adopting the ARMA model can effectively improve the accuracy of long-term SCB prediction.     

Density models for the upper atmosphere

Modeling the effects of atmospheric drag is one of the more important problems associated with the determination of the orbit of a near-earth satellite. Errors in the drag model can lead to significant errors in the determination and prediction of the satellite motion. The uncertainty in the drag acceleration can be attributed to three separate effects: (a) errors in the atmospheric density model, (b) errors in the ballistic coefficient, and (c) errors in the satellite relative velocity. In a number of contemporary satellite missions, the requirements for performing the orbit determination and predictions in near real-time has placed an emphasis on density model computation time as well as the model accuracy. In this investigation, a comparison is made of three contemporary atmospheric density models which are candidates for meeting the current orbit computation requirements. The models considered are the analytic Jacchia-Roberts model, the modified Harris-Priester model, and the USSR Cosmos satellite derived density model. The computational characteristics of each of the models are compared and a modification to the modified Harris-Priester model is proposed which improves its ability to represent the diurnal variation in the atmospheric density.This investigation was supported by the NASA Goddard Spaceflight Center under contract NAS5-20946 and Contract NSG 5154.     

Comparison of BDS Station Clock Short-term Prediction Models and their Applications in Precise Orbit Determination

BDS (BeiDou Navigation Satellite System) ground tracking stations are equipped with high accuracy atomic clocks, and they are synchronized with the BDS time scale (BDT) via the Precise Orbit Determination (POD) processing. During the periods of satellite maneuver and post-maneuver, station clocks are kept fixed as known values in the POD processing. To improve the real-time POD capability, station clocks need to be predicted. In this paper, the performance of three clock prediction models is evaluated, including quadratic polynomial model (QP), periodical term model (PM), and grey model (GM). The precision of clock fitting and prediction, as well as the performance of the prediction models in POD are compared. Data of six stations are used for test, and the results show that: the mean fitting accuracy of quadratic polynomial model, periodical term model, and grey model is 0.14 ns, 0.05 ns, 0.27 ns, respectively; the 1 h and 2 h prediction precision of the three models is 1.17 ns, 0.88 ns, 1.28 ns, and 2.72 ns, 2.09 ns, 2.53 ns, respectively. Applying the 1 h and 2 h predicted station clocks in the POD, the 3D orbit accuracy reaches the best using the periodical term model, while the radial accuracy of satellite orbit is rather close for the three models with the difference within 3 cm.     

基于卡尔曼滤波的脉冲星计时研究

脉冲星是高速自转的中子星,其自转周期稳定,不受人为干扰破坏,可作为绝对时间的参考量.论文提出一种基于卡尔曼滤波算法的脉冲星授时方法,以太阳某同步轨道为例,对基于卡尔曼滤波的钟差控制以及脉冲星星表误差和脉冲到达时间(TOA)测量精度对授时精度的影响进行了仿真分析.结果表明,该方法可以有效消除星载时钟钟差并抑制其随时间的增加,解决了航天器搭载低成本时钟精度不能满足要求的问题.     

Analysis of the Precision of Pulsar Time Clock Modeltwo

Millisecond pulsars have a very high rotation stability, which can be applied to many research fields, such as the establishment of the pulsar time standard, the detection of gravitational wave, the spacecraft navigation by using X-ray pulsars and so on. In this paper, we employ two millisecond pulsars PSR J0437-4715 and J1713+0743, which are observed by the International Pulsar Timing Array (IPTA), to analyze the precision of pulsar clock parameter and the prediction accuracy of pulse time of arrival (TOA). It is found that the uncertainty of spin frequency is 10^?15 Hz, the uncertainty of the first derivative of spin frequency is 10^?23 s^?2, and the precision of measured rotational parameters increases by one order of magnitude with the accumulated observational data every 4～5 years. In addition, the errors of TOAs within 4.8 yr which are predicted by the clock model established by the 10 yr data of J0437-4715 are less than 1 μs. Therefore, one can use the pulsar time standard to calibrate the atomic clock, and make the atomic time deviate from the TT (Terrestrial Time) less than 1 μs within 4.8 yr.     

附有周期项的预报模型及其在GPS卫星钟差预报中的应用研究

为了有效进行GPS卫星钟差预报和更好地反映卫星钟差特性,除了考虑卫星原子钟频移、频漂和频漂率等物理性质外,还应考虑到卫星钟差的周期性变化特点.在二次多项式模型基础上,增加了周期项因素,构造了新的预报模型.选取部分GPS卫星铯钟(Cs.clock)和铷钟(Rb.clock)钟差资料,根据钟差变化趋势分3种情况,按不同时间长度进行钟差预报分析,并与二次多项式模型的预报结果比较分析,大量数据分析表明:附有周期项的二次多项式模型预报精度优于二次多项式模型,铷钟预报精度略优于铯钟.     

测定天文大气折射和建立电磁波折射延迟实测模型(Ⅲ)-专用测量仪器

针对用天文大气折射测定值,建立随观测站和随方位而异的电磁波折射延迟改正模型的高精度要求,提出了新的仪器误差理论,其主要内容是允许仪器误差存在,并看成是不断变化的,采用相应的测量方法作实时的测定和修正,同时消除仪器的各种变形和误差的影响,排除观测数据中的各种系统误差来源,并达到提高单次测定精度目的;文中还针对不同纬度的观测站、多方位、从天顶直到低空的观测需要,给出了仪器总体结构的安排,和采用视频CCD作为接收器的终端设计方案,也给出了各种仪器误差的测定方法和测量装置的设计要求。     

基于混沌时间序列的Volterra自适应滤波极移预报方法

针对极移复杂的时变特性, 根据混沌相空间坐标延迟重构理论, 提出一种基于Volterra自适应滤波的极移预报方法. 首先, 利用最小二乘拟合算法分离极移序列中的线性趋势项、钱德勒项和周年项, 获得线性极移、钱德勒极移和周年极移的外推值; 其次, 通过C-C关联积分法对最小二乘拟合残差序列进行相空间重构, 并利用小数据量法计算残差序列的最大Lyapunov指数验证其混沌特性, 在此基础上, 构建Volterra自适应滤波器对残差序列进行预测; 最后, 将线性极移、钱德勒极移和周年极移的外推值以及最小二乘拟合残差的预测值相加获得极移最终预报值. 利用国际地球自转服务局(International Earth Rotation and Reference Systems Service, IERS)提供的极移数据进行1--60d跨度预报, 并将预报结果分别与国际地球定向参数预报比较竞赛(Earth Orientation Parameters Prediction Comparison Campaign, EOP PCC)结果和IERS A公报发布的极移预报产品进行对比, 结果表明: 对于1--30d的短期预报, 该方法的预报精度与EOP PCC最优预报方法相当, 当预报跨度超过30d时, 该方法的预报精度低于EOP PCC最优预报方法, 优于参与EOP PCC的其他方法; 与IERS A公报相比, 该方法的短期预报效果较好, 当预报跨度增加时预报精度低于IERS A公报. 预报结果表明该方法更适合于极移短期预报.     

Short-Term Solar Flare Prediction Using Predictor Teams

A short-term solar flare prediction model is built using predictor teams rather than an individual set of predictors. The information provided by the set of predictors could be redundant. So it is necessary to generate subsets of predictors which can keep the information constant. These subsets are called predictor teams. In the framework of rough set theory, predictor teams are constructed from sequences of the maximum horizontal gradient, the length of neutral line and the number of singular points extracted from SOHO/MDI longitudinal magnetograms. Because of the instability of the decision tree algorithm, prediction models generated by the C4.5 decision tree for different predictor teams are diverse. The flaring sample, which is incorrectly predicted by one model, can be correctly forecasted by another one. So these base prediction models are used to construct an ensemble prediction model of solar flares by the majority voting rule. The experimental results show that the predictor team can keep the distinguishability of the original set, and the ensemble prediction model can obtain better performance than the model based on the individual set of predictors.     

Evolution of the cluster abundance in non-Gaussian models

We carry out N -body simulations of several non-Gaussian structure formation models, including Peebles' isocurvature cold dark matter model, cosmic string models, and a model with primordial voids. We compare the evolution of the cluster mass function in these simulations with that predicted by a modified version of the Press–Schechter formalism. We find that the Press–Schechter formula can accurately fit the cluster evolution over a wide range of redshifts for all of the models considered, with typical errors in the mass function of less than 25 per cent, considerably smaller than the amount by which predictions for different models may differ. This work demonstrates that the Press–Schechter formalism can be used to place strong model-independent constraints on non-Gaussianity in the Universe.     

A Volterra Adaptive Filtering Method for Polar Motion Prediction Based on Chaotic Time Series

In consideration of the complex time-varying characteristics of polar motion (PM), this paper takes PM as chaotic time series. A Volterra adaptive filter is employed for predicting PM based on the state space reconstruction of delay-coordinate embedding of dynamic system. This method first uses the Least Squares (LS) technology to estimate the harmonic models for the linear trend, Annual and Chandler Wobbles (AW and CW) in PM. The selected LS deterministic models are subsequently used to extrapolate the linear trend, AW, and CW, and obtain the LS residues (the difference between the LS model and PM data themselves). Secondly, the phase space and largest Lyapunov exponent of the LS residues are reconstructed, and calculated by means of the C-C and small data-set algorithm, respectively. Further, a Volterra adaptive filter is designed for generating the extrapolations of the LS residues. The extrapolated LS residues are then added to the LS deterministic models in order to obtain the predicted PM values. The EOP C04 time series released by the International Earth Rotation and Reference Systems Service (IERS) are selected as data base to generate the PM predictions up to 60 days in the future. The results of the predictions are analyzed and compared with those obtained by the Earth Orientation Parameters Prediction Comparison Campaign (EOP PCC) and IERS Bulletin A. The results show that the accuracy of the predictions up to 30 days is comparable with that by the most accurate prediction techniques participating in the EOP PCC for PM, but worse than that by those most accurate techniques beyond 30 days in the future. The results also illustrate that the short-term predictions are better than those published by the IERS Bulletin A. However, the errors of the predictions rapidly increase with the prediction days. It is therefore concluded that the proposed method is a potential technology for short-term PM prediction.     

The Model of Radio Two-way Time Comparison between Satellite and Station and Experimental Analysis

Time synchronization between satellite and station is the key technique of satellite navigation system and the foundation of realization of satellite navigation and positioning. Aiming at solving the problems of time synchronization, we have discussed a new method of radio two-way time comparison between satellite and station, deduced in detail the reduction model of up- and down-link pseudo ranges between satellite and station, and provided a practical calculation model of clock error between satellite and station. By calculating the differences between up- and down-link pseudo ranges, this method has eliminated the influences of common errors, such as the tropospheric delay, satellite ephemeris errors, ground station coordinates errors and so on. The ionospheric delay relevant to signal frequency is also weakened largely, thus this improves the accuracy of time comparison greatly. Finally, experimental analysis is conducted by using observational data, and the results show that the accuracy of radio two-way time comparison between satellite and station can attain about 0.34 ns, which validates the correctness of theoretical method and model.     

基于深度学习的太阳F_10.7辐射通量的短期预报研究

F_10.7太阳辐射通量作为输入参数被广泛运用于大气经验模型、电离层模型等空间环境模型,其预报精度直接影响航天器轨道预报精度.采用时间序列法统计了太阳辐射通量F10.7指数和太阳黑子数(SSN)的关系,给出了两者之间的线性关系,在此基础上提出了一种基于长短时记忆神经网络(Long and Short Term Memory,LSTM)的预报方法,方法结合了54 d太阳辐射通量指数和SSN历史数据来对F_10.7进行未来7 d短期预报,并与其他预报方法的预报结果进行了比较,结果表明:(1)所建短期预报7 d方法模型的性能优于美国空间天气预报中心(Space Weather Prediction Center, SWPC)的方法,预测值和观测值的相关系数(CC)达到0.96,同时其均方根误差约为11.62个太阳辐射通量单位(sfu),预报结果的均方根误差(RMSE)低于SWPC,下降约11%;(2)对预测的23、24周太阳活动年结果统计表明,太阳活动高年的第7 d F10.7指数预报平均绝对百分比误差(MAPE)最优可达12.9%以内,低年最优可达2...     

Analysis of the wide area differential correction for BeiDou global satellite navigation system

The regional BeiDou Satellite System, or BDS2, broadcasts a differential correction as Equivalent Satellite Clock Correction to correct both orbit and satellite clock errors. For the global BDS, or BDS3, satellite orbit and clock corrections conforming with RTCA standards will be broadcast to authorized users. The hybrid constellation and regional monitoring network pose challenges for the high precision separation of orbit and satellite clock corrections. Three correction models of kinematic,dynamic and Two-way Satellite Time Frequency Transfer(TWSTFT)-based dynamic were studied to estimate the satellite orbit and clock corrections. The correction accuracy of the three models is compared and analyzed based on the BDS observation data. Results show that the accuracies(root mean square, RMS) of dual-frequency real-time positioning for the three models are about 1.76 m, 1.78 m and 2.08 m respectively, which are comparable with the performance of WAAS and EGNOS. With dynamic corrections, the precision of Precise Point Positioning(PPP) experiments may reach about 23 cm after convergence.     

基于历史TLE的空间目标轨道预报误差演化规律研究

北美防空司令部(North American Aerospace Defense Command, NORAD)发布的双行根数(Two Line Element, TLE)是广大航天工作者最常用的轨道根数,与其对应的轨道模型是SGP4/SDP4 (Simplified General Perturbation Version 4/Simplified Deep-space Perturbation Version 4)解析模型.由于TLE中并没有包含相应的轨道精度信息,编目轨道的应用范围受到很大的限制.基于Space-Track网站发布的历史TLE数据和配套的SGP4/SDP4动力学模型,采用定轨标预报的方法统计并生成了大量目标轨道的预报误差,通过对预报轨道的时间区间划分给出了每个目标的预报误差随预报时间变化的拟合系数,并进一步对不同类型轨道预报误差的演化规律和特征进行了分类讨论,给出了4种轨道类型目标的轨道预报误差随时间演化的平均解析模型,为拓展双行根数的应用提供有价值的参考.