北斗广域高精度时间服务原型系统

基于精密单点定位(precise point positioning,PPP)的时间传递技术以其精度高、覆盖范围广的优点成为性能最优的GNSS时间传递方法之一。随着广域差分产品时效性的提高,实时PPP时间传递开始应用于精密授时的研究。本文在PPP时间传递技术的基础上,结合实时卫星钟差估计、接收机时钟调控及硬件延迟标校技术,建立了基于北斗卫星导航系统(BeiDou navigation satellite system,BDS)的广域高精度时间服务(wide-area precise timing,WPT)系统,可为用户实时提供准确、稳定、可溯源的时间。WPT系统分为时间服务平台和用户终端两个部分。时间服务平台引入高精度的时间作为系统的参考时间基准,并提供广域实时差分改正数;用户终端基于实时PPP时间传递算法获取本地钟与系统时间基准的差异,并采用精密调钟技术实现终端与系统的同步。为了验证系统的实时授时性能,本文进行了零基线、短基线及广域环境下的性能测试和评估。试验结果表明,该系统零基线、短基线时间同步精度优于0.5 ns,广域条件下单天的授时精度均优于1 ns,为基于北斗系统的精密授时技...     

基于衰减记忆思想的故障容错方法

残差χ2法难以准确检测小幅值突变故障,改进的序贯概率比检测(SPRT)方法通过迭代递推,能够检测到故障,但存在延时且对故障结束不敏感。基于此,本文给出了区分故障大小的方法,针对小幅值故障提出了一种基于衰减记忆思想的故障容错方法:当改进的SPRT方法检测到故障后,对系统进行隔离重构,用不包含故障信息的数据进行量测更新,利用衰减因数减小包含故障信息的陈旧滤波值的权重,以提高滤波精度,同时构造"伪正常"状态,使该方法能够及时判断故障结束。仿真结果表明,本文提出的方法适用于故障多发的情形,能够提高滤波精度,增强系统可靠性。     

Inpho地理建模在河道断面测量中的应用研究

主要介绍了Inpho全数字摄影测量系统在黑龙江省干流河道断面测量项目的应用,充分挖掘Inpho系统在坐标系统定义、立体建模等方面的巨大优势,通过不同试验数据的对比分析,验证Inpho系统在各个环节的数据处理精度,以满足项目生产要求,保证项目顺利开展。     

DMCⅢ航空数码影像匀光算法研究

DMCⅢ航空数码相机采用了新型的面阵CMOS传感器代替了原来的CCD传感器,导致影像亮度不平衡,严重影响了后期的空三加密工作。Wallis匀光算法主要用于多幅影像间的差异调整,能够有效地解决DMCⅢ影像的质量问题。本文详细地阐述了DMCⅢ影像的Wallis匀光算法,并结合实例进行验证,匀光效果理想。     

A review on the inter-frequency biases of GLONASS carrier-phase data

GLONASS ambiguity resolution (AR) between inhomogeneous stations requires correction of inter-frequency phase biases (IFPBs) (a “station” here is an integral ensemble of a receiver, an antenna, firmware, etc.). It has been elucidated that IFPBs as a linear function of channel numbers are not physical in nature, but actually originate in differential code-phase biases (DCPBs). Although IFPBs have been prevalently recognized, an unanswered question is whether IFPBs and DCPBs are equivalent in enabling GLONASS AR. Besides, general strategies for the DCPB estimation across a large network of heterogeneous stations are still under investigation within the GNSS community, such as whether one DCPB per receiver type (rather than individual stations) suffices, as tentatively suggested by the IGS (International GNSS Service), and what accuracy we are able to and ought to achieve for DCPB products. In this study, we review the concept of DCPBs and point out that IFPBs are only approximate derivations from DCPBs, and are potentially problematic if carrier-phase hardware biases differ by up to several millimeters across frequency channels. We further stress the station and observable specific properties of DCPBs which cannot be thoughtlessly ignored as conducted conventionally. With 212 days of data from 200 European stations, we estimated DCPBs per stations by resolving ionosphere-free ambiguities of \(\sim \)5.3 cm wavelengths, and compared them to the presumed truth benchmarks computed directly with L1 and L2 data on ultra-short baselines. On average, the accuracy of our DCPB products is around 0.7 ns in RMS. According to this uncertainty estimates, we could unambiguously confirm that DCPBs can typically differ substantially by up to 30 ns among receivers of identical types and over 10 ns across different observables. In contrast, a DCPB error of more than 6 ns will decrease the fixing rate of ionosphere-free ambiguities by over 20 %, due to their smallest frequency spacing and highest sensitivity to DCPB errors. Therefore, we suggest that (1) the rigorous DCPB model should be implemented instead of the classic, but inaccurate IFPB model; (2) DCPBs of sub-ns accuracy can be achieved over a large network by efficiently resolving ionosphere-free ambiguities; (3) DCPBs should be estimated and applied on account of their station and observable specific properties, especially for ambiguities of short wavelengths.     

国家高精度GPS网整体平差中的粗差分析

分析了国家高精度GPS网中的粗差观测量的特点,提出了采用相关分析的粗差探测理论,对国家高精度GPS网的各子网和相邻子网进行粗差探测,并采用稳健估计的平差方法,消除粗差对平差结果的影响,大大提高了国家高精度GPS网的整体平差精度。     

基于短时间序列重力观测数据的潮汐改正方法

对于没有长期连续潮汐观测站和无精密潮汐模型的地区,研究高精度潮汐改正方法具有重要意义。给出了基于短时间序列重力观测数据的高精度潮汐改正方法,并利用全球动力学计划中TIGOConcepcion、Kamio-ka和Hsinchu三个台站的超导重力观测数据对该方法进行了试验分析。研究结果表明,利用一天或数天重力观测数据可建立高精度潮汐模型,其振幅因子和相位延迟解算精度分别优于0.01和0.5°,潮汐改正精度可以达到μGal量级,验证了该方法的正确性和有效性。本文方法为无精密潮汐模型区域的潮汐改正提供了新的途径。     

小波时变参数PGM(1,1)模型的工程应用研究

首先阐述了小波去除数据噪声的方法及小波模型的选取问题,然后对GM(1,1)模型背景值生成序列进行改进,采用搜索法确定背景值最佳生成系数.考虑到模型中的灰参数会随时间而变化,采用多项式逼近模型灰参数,并通过最小二乘方法求解多项式的系数,最后形成了小波时变参数PGM(1,1)模型同时采用Runge-Kutta方法求解.通过武成城际铁路沉降监测数据的计算分析表明,小波时变参数PGM(1,1)在高铁沉降预测中具有较高的精度.     

基于小波去噪的高铁沉降预测模型研究

以武汉市某高铁的沉降观测数据为基础,对小波去噪前后的观测数据分别采用非线性曲线拟合模型和时间序列分析模型进行建模预测,并与实测数据进行比较分析.结果表明,观测数据经小波去噪后再进行建模分析,两种方法的预测精度都有很大改善,对高铁沉降变形预报有一定的实用价值.     

基于SINEX文件的ERP参数估计

利用IGS所发布的对GPS全球站处理后形成的单天解SINEX文件,通过参数转换和附有限制条件的间接平差两种不同的思路,详细推导了ERP参数的估计方法。并给出了利用自编程序估计的结果与IERS所发布的结果的比较,发现单纯利用GPS观测结果进行ERP参数的估计可能存在残留的系统性偏差。