一种网络RTK对流层斜延迟的估计方法

针对网络RTK数据处理方法中,卫星高度角较低时湿分量映射函数误差较大所引起的问题,提出了一种直接估计斜方向对流层湿延迟的网络RTK数据处理方法,并通过试验对该方法的效果进行分析.在该方法中,斜方向湿延迟直接作为参数进行估计,通过增加虚拟观测引入不同卫星湿延迟参数间的相关性,通过建立适当的状态转移模型引入同一卫星湿延迟参数历元间的相关性.实验结果表明,该方法能精确估计对流层湿延迟,降低了对流层延迟对模糊度估计的影响,提高了网络RTK数据处理的质量.     

GPS精密单点定位中对流层延迟处理方法研究

本文首先介绍了GPS精密单点定位技术,采用宽巷组合的方法得到观测方程。然后对精密定位中的误差改正作了简述,主要讨论了处理对流层延迟的Saastamoinen模型和Niell映射函数。提出用扩展卡尔曼滤波参数估计方法来处理对流层延迟,通过实例用Saastamoinen模型、Saastamoinen模型加Niell映射函数和扩展卡尔曼滤波参数估计三种方法对对流层延迟进行改正,结果表明该方法优于Saastamoinen模型。     

对流层改正模型在双差RTK解算中的精度影响分析

正GPS信号通过对流层时,传播的路径发生弯曲,从而使测量距离产生偏差,这种现象叫作对流层延迟。准确估计出用户与主参考站之间的对流层延迟是网络RTK高精度实时定位的关键因素。目前天顶延迟采用对流层模型,如Saastamoinen、Hopfield、UNB3m等进行求解,而GMF映射函数和VMF1映射函数是被主流解算软件所选用的映射函数。理论分析和实践证明,目前采用上述几种对     

顾及大气延迟误差的中长基线RTK算法

针对常规RTK作业距离一般不超过15km的问题,提出了一种顾及大气延迟误差的中长基线RTK的算法,突破了常规RTK作业距离。在中长基线情况下,与大气延迟有关的误差如电离层延迟误差、对流层延迟误差等,随着基线长度的增加,空间相关性大大降低,进而影响整周模糊度的快速解算。基于卡尔曼滤波算法,采用非组合差分定位模型,对于电离层延迟误差采用了电离层加权模型进行估计,对于对流层延迟分别采用了相对对流层延迟参数估计和绝对天顶对流层参数估计。最终通过实测数据对该算法进行了算法验证和结果分析。试验结果表明:该算法可以实现中长基线RTK的快速解算,并且在估计相对对流层延迟时,绝对天顶对流层参数估计不利于基准站和流动站的对流层延迟分离,一般采用估计流动站上的相对对流层延迟。     

一种顾及对流层残余延迟的GNSS随机建模方法

针对常用的基于高度角和信噪比的经验模型难以客观地体现未建模误差影响的问题,基于卫星高度角与大气层延迟残留误差具有强相关性的思想,提出了一种基于天顶映射函数的随机模型。该模型中卫星的方差通过卫星信号在对流层中的传播距离与对流层天顶高度的比值给出,更准确地体现了信号在对流层中的传播距离越长,则对流层残余延迟越高,观测量方差应该越大。实验表明,各随机模型均能够在不同程度上反映定位精度的高低,相比于传统的随机模型,天顶映射函数模型能够显著提高定位精度,为精密单点定位精度的进一步提高提供了理论基础。     

对流层映射函数对南极地区GPS基线解算的影响

映射函数是将对流层模型得到的天顶延迟准确转化为传播路径延迟的关键,选择合适的映射函数对于对流层模型的准确性和GPS定位精度的提高有着十分重要的意义。本文介绍了NMF、VMF1和GMF 3种映射函数,采用我国南极中山站、长城站及南极大陆周边IGS站的数据,通过计算比较了3种映射函数在南极地区对GPS基线解算的影响。结果表明,在南极地区进行GPS基线解算时,采用NMF函数产生的误差最大,VMF1与GMF的结果则更加精确,VMF1的效果略好于GMF。     

海道测量定位中对流层延迟差分估计技术研究

为削弱海上对流层延迟对高精度海道测量的影响,提出了一种基于差分改正思想的对流层延迟估计方法。首先,以Saastamoinen模型作为先验值,采用精密单点定位技术估算对流层改正量。将天顶延迟的剩余误差作为待定参数,用Kalman滤波估计对流层的残余量;然后,分别估计基准站和移动站的对流层延迟,作为差分计算的初值代入差分解算模型中,从而求得海上移动站的精确位置。实测数据表明,相对于常规动态解,基于对流层差分改正的定位技术改善了移动站的定位精度,其中,垂直方向的精度提高了17.6%。     

基于映射函数网络RTK的大气误差内插估计模型

在比较分析已有内插模型的基础上,以卫星高度角、参考站高程、距离为变量,以大气映射函数为基本模型,提出了一种新的适用于高程差异大的大气误差内插模型。利用江苏连续运行参考站系统部分参考站数据,采用不同的内插模型进行处理、比较与分析。结果表明,对于高程差异大、卫星高度角小的用户站,映射函数估计方法、低阶曲面模型能够准确地估计出其与主参考站之间双差对流层误差,其最大均方差不超过2cm;映射函数估计双差电离层误差方法与低阶曲面模型、线性内插模型的估计精度相当。在以上4种方法的比较中,距离线性内插模型的估计精度最差,将近5cm。     

CORS站数据解算中对流层映射函数影响分析

针对不同对流层映射函数对CORS站数据解算的影响,为获知适用于我国东北部地区的对流层延迟解算策略,就CORS站数据解算中所使用的对流层映射函数进行比较分析。结论:随着卫星高度截止角的增大,NMF映射函数下NRMS值逐渐优于GMF和VMF1下的NRMS值。处理数据量大的CORS站数据,GMF映射函数具有最佳的改正效果,对我国北斗导航定位系统应用映射函数具有参考价值。     

高精度GNSS服务中对流层映射函数的影响性分析

针对GNSS服务中如何获取高精度的大地高以及GNSS气象中对流层湿延迟项,文中采用3种试验方案,利用对流层变化复杂的香港区域CORS,分析不同映射函数存不同高度角时对精密服务的影响。结果表明：存高度角为15°时VMFl、GMF、NMF映射函数获取基线重复性相当,天顶延迟变化规律一致;在低高度角为10°时,基于VMFl映射函数的基线重复率更好,对大气变化的敏感性更强,GMF映射函数获取的天顶延迟精度较好,NMF映射函数获取的精度较弱。     

A real-time meteorological-based troposphere (RMT) correction with integrity bound for long baseline DGPS

This paper concentrates on the analysis of a real-time meteorological (MET)-based troposphere (RMT) model where MET data are used in real-time to provide troposphere error corrections with a bounded level of integrity for a prototype National Differential Global Positioning System-High Performance (NDGPS-HP) architecture. Toward this goal, three aspects are studied for this approach: sensitivity analysis, accuracy assessment, and integrity analysis. A Hopfield zenith delay and Chao mapping function models were chosen as a good compromise between accuracy and complexity in the integrity analysis. The sensitivity analysis results indicate that the Hopfield model is mostly sensitive to hot humid conditions, which is compounded slightly more and where some relative humidity sensors are less accurate. The accuracy assessment was performed with respect to both absolute and relative accuracy. In the absolute accuracy assessment, the comparison was made in terms of zenith troposphere delay estimation error, with respect to the International GPS Service (IGS) final troposphere zenith path delay (ZPD) product, which was used as the true ZPD. For locations where IGS stations are not available, a relative accuracy assessment was performed whereby comparisons were made in terms of GPS double difference (DD) carrier-phase troposphere correction residuals using various techniques. The accuracy assessment results indicate that the RMT has insignificant differences from the prototype National Oceanic and Atmosphere Administration (NOAA) troposphere error forecast model. An integrity analysis was performed, which presents integrity bounds for the RMT that can be applied to a NDGPS-HP architecture in which integrity requirements exist. The overriding goal of this effort was to establish a preliminary real-time troposphere error estimation model, with defined levels of integrity in its troposphere error estimation that can be included in an NDGPS-HP architecture, where integrity is a key system requirement. The conclusion is drawn that the RMT model may be well suited for a variety of users within a NDGPS-HP architecture. An erratum to this article can be found at     

虚拟参考站对流层延迟算法

在VRS定位中,对影响虚拟站精度的对流层延迟仅是采取简单的基于参考站对流层延迟的几何距离内插模型,虽然此模型较简单,但是精度较差,不利于提高定位精度。因此,本文提出了一种考虑气象元素、纬度和高程对对流层的影响,结合数值气象学内插气象元素的方法,利用经典的对流层HOPFIELD模型以及MTT映射函数,估算出测站点的对流层延迟,通过数值分析,证明了此方法的可行性;特别是在低高度角的情况下,与传统方法相比,在精度及稳定性上有一定的提高。     

Accuracy improvement of zenith tropospheric delay estimation based on GPS precise point positioning algorithm

In the precise point positioning(PPP),some impossible accurately simulated systematic errors still remained in the GPS observations and will inevitably degrade the precision of zenith tropospheric delay(ZTD) estimation.The stochastic models used in the GPS PPP mode are compared.In this paper,the research results show that the precision of PPP-derived ZTD can be obviously improved through selecting a suitable stochastic model for GPS measurements.Low-elevation observations can cover more troposphere informat...     

大气折射延迟映射函数的比较

简要综述对流层大气折射延迟的基本概念,对几种常用的连分式的映射函数进行比较,结果表明映射函数模型在低高度角呈现较大的差异性,说明利用映射函数模型对大气折射进行改正有很多局限性。     

基于滤波及起算数据误差的验后估计法

针对起算数据具有误差时现有处理方法的缺陷,巧妙地利用了真值和估值之间的关系处理起算数据误差,提出了基于滤波的顾及起算数据误差的验后估计法,剔除了起算数据误差的影响,得出相对于起算数据误差基准的平差结果。平差计算与随机模型的验后估计同时进行,使数据处理得更加完善。     

VLBI-derived troposphere parameters during CONT08

Time-series of zenith wet and total troposphere delays as well as north and east gradients are compared, and zenith total delays (ZTD) are combined on the level of parameter estimates. Input data sets are provided by ten Analysis Centers (ACs) of the International VLBI Service for Geodesy and Astrometry (IVS) for the CONT08 campaign (12?C26 August 2008). The inconsistent usage of meteorological data and models, such as mapping functions, causes systematics among the ACs, and differing parameterizations and constraints add noise to the troposphere parameter estimates. The empirical standard deviation of ZTD among the ACs with regard to an unweighted mean is 4.6?mm. The ratio of the analysis noise to the observation noise assessed by the operator/software impact (OSI) model is about 2.5. These and other effects have to be accounted for to improve the intra-technique combination of VLBI-derived troposphere parameters. While the largest systematics caused by inconsistent usage of meteorological data can be avoided and the application of different mapping functions can be considered by applying empirical corrections, the noise has to be modeled in the stochastic model of intra-technique combination. The application of different stochastic models shows no significant effects on the combined parameters but results in different mean formal errors: the mean formal errors of the combined ZTD are 2.3?mm (unweighted), 4.4?mm (diagonal), 8.6?mm [variance component (VC) estimation], and 8.6?mm (operator/software impact, OSI). On the one hand, the OSI model, i.e. the inclusion of off-diagonal elements in the cofactor-matrix, considers the reapplication of observations yielding a factor of about two for mean formal errors as compared to the diagonal approach. On the other hand, the combination based on VC estimation shows large differences among the VCs and exhibits a comparable scaling of formal errors. Thus, for the combination of troposphere parameters a combination of the two extensions of the stochastic model is recommended.     

大范围网络RTK基准站间整周模糊度实时快速解算

网络RTK是目前实现高精度实时动态定位的重要手段之一,而网络RTK高精度定位的关键问题是基准站间整周模糊度的实时快速准确固定。对于大范围网络RTK,由于基准站间距离的增加,电离层延迟误差、对流层延迟误差和卫星轨道误差相关性降低,导致基准站间整周模糊度不能快速准确地固定,因此本文提出了一种大范围网络RTK基准站间整周模糊度固定算法。该算法首先利用L1、L2载波相位观测值和P1、P2伪距观测值解算基准站间的双差宽巷模糊度;然后采用Saastamoinen模型和Chao映射函数模型相结合解算双差对流层延迟误差,并将双差宽巷模糊度作为L1、L2双差载波相位整周模糊度的约束关系来确定L1、L2双差载波相位整周模糊度;最后采用CORS站的实测数据进行试验,并将本文的试验结果同GAMIT软件的解算结果进行比对,结果表明该算法可以快速准确地实现单历元双差载波相位整周模糊度的固定。