利用IVS加强观测确定UT1的分析研究

首先对IVS(International VLBI Service for Astrometry and Geodesy)UT1加强观测的历史发展和总体情况进行了比较详细的介绍,对目前加强观测中存在的问题进行了比较全面的分析;在此基础上对IVS从1984年2月到2011年8月全部的加强观测数据进行了综合处理,进一步分析了加强观测解算UT1的历史改进和目前的解算能力,对比分析不同类型加强观测的UT1结果,发现不同观测网之间存在数十微秒水平的差异;并着重分析了上海佘山站参与的加强观测的解算结果,分析表明上海佘山站在IVS加强观测中与其他参与台站具有相同的测量能力.总体而言,目前IVS加强观测确定的UT1与IERS(International Earth Rotaion Service)C04之间存在约10μs水平的不确定性.     

基于天文开源软件的卫星干涉测量数据处理系统

VLBI (Very Long Baseline Interferometry)技术观测卫星需要对干涉测量数据进行相关和后处理,通过相关、时延校准、条纹搜索,最终得到卫星的基线几何时延.基于天文开源软件建立起一套卫星干涉测量数据处理系统.该系统可工作在实时和事后两种状态,实现相关、中性大气、电离层、钟模型以及仪器硬件的时延校准、条纹搜索、生成基线时延和时延率序列.使用该系统处理北斗GEO (Geosynchronous Earth Orbit)卫星的干涉测量试验数据,得到了精度在1–2 ns量级的卫星基线时延序列.     

基于高斯过程的日长变化预报

由于日长(length-of-day,LOD)变化具有复杂的时变特性,传统线性模型如最小二乘外推模型、时间序列分析模型等的预报效果往往不甚理想,所以将一种新型的机器学习算法—高斯过程(Gaussian processes,GP)方法用于LOD变化预报,并将预报结果同利用反向传播神经网络(back propagation neural networks,BPNN)和广义回归神经网络(general regression neural networks,GRNN)的预报结果以及地球定向参数预报比较竞赛(Earth Orientation Parameters Prediction Comparison Campaign,EOP PCC)的预报结果进行对比.结果表明,GP用于LOD变化预报是高效可行的.     

极潮对VLBI测定基线的影响

本估计了极潮对VLBI测定基线的影响，计算结果表明，地球自转变化和极移引起的极潮对测站径向位移最大影响分别约为0.4mm和16.1mm；对测站水平位移最大值分别近似为0.1mm和4.5mm。采用1989年的EOP参数分别对上海与西德Wettzell、澳大利亚Canberra、日本Kashima和美国Kauai四个站的基线变化计算表明，极潮引起四条基线变化的幅值分别为12.9mm、18.5mm、2.1mm和14.9mm，引起国内上海、昆明和乌鲁木齐三站基线的变化分别可达3－6mm。进一步对极潮的次级效应计算表明，海洋极潮引起上述国内三站的负荷垂直位移最大值分别为0.87mm、054mm和0.48mm。因此，采用毫米级精度的VLBI技术用于天体测量学和大地测量学研究，在归算模型中应考虑极潮的影响。     

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...     

基于双谱滤波的综合脉冲星时算法研究

毫秒脉冲星的自转频率非常稳定,提供了一种独立的基于遥远自然天体并能持续数百万乃至数十亿年的时间基准,具有稳定性强、运行时间长、服务范围广等特点.为了减弱毫秒脉冲星计时观测中各种高斯噪声对脉冲星时的影响,研究了一种基于双谱滤波的综合脉冲星时构建算法,处理分析了国际脉冲星计时阵(International Pul-sar Timing Array,IPTA)最新发布的4颗毫秒脉冲星(PSR J0437-4715、J0613-0200、J1713+0747和J1909-3744)的观测数据,分析了不同时间尺度综合脉冲星时的稳定性,并与构成国际原子时(International Atomic Time,TAI)的4家授时单位原子钟稳定性进行了比较.结果表明:双谱滤波算法能够较好地抑制观测噪声,提高综合脉冲星时的稳定性.相比于经典加权算法,综合脉冲星时1 yr、10 yr稳定度从7.77×10^-14、8.56×10^-16分别提高到1.50×10^-14、3.50×10^-16,单脉冲星时稳定性的提升也类似.同时发现,综合脉冲星时稳定性在5 yr及以上时间尺度上优于原子钟稳定性,可用于改善当前原子时的长期稳定性.     

基于小波分析和神经网络的卫星钟差预报性能分析

为了有效地进行卫星钟差预报和更好地反映卫星钟差特性,提出了一种基于小波分析和神经网络的4阶段混合模型来实现卫星钟差的预报,并给出了基于小波分析和径向基函数(Radial Basis Function,RBF)神经网络进行卫星钟差预报的基本思想、预报模型和实施步骤.采用"滑动窗"划分数据,利用神经网络预测小波分解和去噪后的钟差序列各层系数,更精确地把握钟差序列复杂细致的变化规律,从而更好地逼近钟差序列.为验证该混合预报模型的可行性和有效性,利用GPS卫星钟差数据进行钟差预报精度分析,并将其与灰色系统模型和神经网络模型进行比较分析.仿真结果显示,该模型具有较好的预报精度,可为实时GPS动态精密单点定位提供较高精度的卫星钟差.     

无人值守GNSS方法测定射电望远镜参考点

为解决常规射电望远镜归心测量工作耗时耗力的问题,引入GNSS (Global Navigation Satellite System)同步监测技术实现了一种针对射电望远镜参考点的无人值守监测方法.设计了针对GNSS靶标点观测数据的归算方法,包括数据匹配、数据检核以及后续精度评估等步骤,并对2018年佘山25-m射电VLBI (Very Long Baseline Interferometry)望远镜的GNSS靶标点实测数据开展了数据预处理、解析与归心解算等,证明了该方法的可行性.结果表明基于该方法,采用单日内部分(5%)数据(约7600个靶标点),所测定的VLBI望远镜参考点的点位形式精度可达3 mm.总结了针对射电望远镜采用GNSS开展无人值守归心测量先行试验中的一些经验教训,明确了利用该方法测量过程中应该注意的问题,为今后更高精度射电望远镜参考点无人值守归心监测提供重要参考.     

高美古观测站大气消光系数测定的初步结果

大气消光系数的测定是天文观测台站一项很重要和基础的工作.介绍了利用新建的2.4 m望远镜在高美古观测站开展的消光系数测定等定标工作的初步结果.利用2009年4～5月对Landolt标准星场的2次测光观测,分别给出了UBVRI 5个波段的消光系数.此外,对该站点大气消光的成分情况进行了探讨.给出的结果与数年前高美古观测站选址时得到的大气消光系数基本一致,并与其它一些知名天文观测台站的消光数据进行了比较.     

2009年7月22日日全食期间VLF信号的异常变化

在2009年7月22日日全食期间,用美国斯坦福大学太阳中心提供的电离层突扰(SID)监测仪对甚低频(VLF)信号进行观测时发现:日全食期间的VLF信号强度变化异常,出现类似日出日落的效应;信号强度振幅变大,类似于雷电效应;而且信号强度在日全食前后一段时间内都有所增强.在对观测数据的可靠性进行充分讨论的基础上,对比以往的观测结果,发现电离层会在日全食发生之前有所变化.     

An Analysis of UT1 Determined by IVS Intensive Observations

In this paper the history and status of the IVS (International VLBI Service for Astrometry and Geodesy) UT1 Intensive observations are briefly re- viewed, and the deficiencies and error sources in the current Intensive observa- tions are investigated. An in-depth analysis of the IVS Intensive observation data from February 1984 to August 2011 with different observation networks is carried out, and the progress of the UT1 accuracy obtained by the Intensive observations during this period is discussed. By comparing the results from dif- ferent networks, a difference of some dozens of microseconds between different networks is found. The results of the IVS Intensive observations with Sheshan Station participated in are analyzed, it shows that the Sheshan Station perfor- mance as well as other stations. Finally, from the comparison and analysis of different UT1 series, it is concluded that there is an uncertainty with a level of 10 microseconds between the UT1 values obtained from the IVS Intensive observations and the values of the IERS (International Earth Rotation Service) C04.     

An adaptive loop gain selection for CLEAN deconvolution algorithm

Radio interferometry significantly improves the resolution of observed images, and the final result also relies heavily on data recovery. The Cotton-Schwab CLEAN(CS-Clean) deconvolution approach is a widely used reconstruction algorithm in the field of radio synthesis imaging. However, parameter tuning for this algorithm has always been a difficult task. Here, its performance is improved by considering some internal characteristics of the data. From a mathematical point of view, a peak signal-to-noise-based(PSNRbased) method was introduced to optimize the step length of the steepest descent method in the recovery process. We also found that the loop gain curve in the new algorithm is a good indicator of parameter tuning.Tests show that the new algorithm can effectively solve the problem of oscillation for a large fixed loop gain and provides a more robust recovery.     

Estimating statistics of sky brightness using radio interferometric observations

Radio interferometers are used to construct high resolution images of the sky at radio frequencies and are the key instruments for accessing the statistical properties of the evolution of neutral hydrogen over cosmic time. Here we use simulated observations of the model sky to assess the efficacy of different estimators of the large-scale structure and power spectrum of the sky brightness distribution. We find that while the large-scale distribution can be reasonably estimated using the reconstructed image from interferometric data, estimates of the power spectrum of the intensity fluctuations calculated from the image are generally biased. This bias is found to be more pronounced for diffuse emission. The visibility based power spectrum estimator, however, gives an unbiased estimate of the true power spectrum. This work demonstrates that for an observation with diffuse emission the reconstructed image can be used to estimate the large-scale distribution of the intensity, while to estimate the power spectrum, visibility based methods should be preferred.With the upcoming experiments aimed at measuring the evolution of the power spectrum of the neutral hydrogen distribution, this is a very important result.     

The Cotton-Schwab Clean At Ultra-High Dynamic Range

We present a study of the dynamic range limitations in images produced with the proposed Square Kilometre Array (SKA) using the Cotton-Schwab CLEAN algorithm for data processing. The study is limited to the case of a small field of view and a snap-shot observation. A new modification of the Cotton-Schwab algorithm involving optimization of the position of clean components is suggested. This algorithm can reach a dynamic range as high as 10⁶ even if the point source lies between image grid points, in contrast to about 10³ for existing CLEAN-based algorithms in the same circumstances. It is shown that the positional accuracy of clean components, floating point precision and the w-term are extremely important at high dynamic range. The influence of these factors can be reduced if the variance of the gradient of the point spread function is minimized during the array design.     

基于线性数据重构的天线动力学模型辨识方法

射电望远镜天线伺服控制系统中的非线性特性, 对系统动力学特性辨识有着显著的影响, 会提高辨识难度, 增加辨识模型的复杂程度. 系统非线性特性的测量与补偿也会增加系统辨识工作量. 针对上述问题, 提出了一种基于非线性采样数据的线性重构方法, 用于动力学特性建模. 通过提取原采样数据的相位与幅值, 对受到噪声与非线性畸变影响的系统采样数据进行线性重构, 降低待辨识模型的复杂度. 搭建了半实物实验平台, 以平台实际采样为基础, 重构线性数据, 利用奇异值法与自回归神经网络评估并辨识平台动力学模型. 实验结果表明, 建模数据奇异值拐点从100阶下降至40阶, 仅用10个神经网络节点200次训练即实现了模型辨识.