The GFZ real-time GNSS precise positioning service system and its adaption for COMPASS

Motivated by the IGS real-time Pilot Project, GFZ has been developing its own real-time precise positioning service for various applications. An operational system at GFZ is now broadcasting real-time orbits, clocks, global ionospheric model, uncalibrated phase delays and regional atmospheric corrections for standard PPP, PPP with ambiguity fixing, single-frequency PPP and regional augmented PPP. To avoid developing various algorithms for different applications, we proposed a uniform algorithm and implemented it into our real-time software. In the new processing scheme, we employed un-differenced raw observations with atmospheric delays as parameters, which are properly constrained by real-time derived global ionospheric model or regional atmospheric corrections and by the empirical characteristics of the atmospheric delay variation in time and space. The positioning performance in terms of convergence time and ambiguity fixing depends mainly on the quality of the received atmospheric information and the spatial and temporal constraints. The un-differenced raw observation model can not only integrate PPP and NRTK into a seamless positioning service, but also syncretize these two techniques into a unique model and algorithm. Furthermore, it is suitable for both dual-frequency and sing-frequency receivers. Based on the real-time data streams from IGS, EUREF and SAPOS reference networks, we can provide services of global precise point positioning (PPP) with 5–10 cm accuracy, PPP with ambiguity-fixing of 2–5 cm accuracy, PPP using single-frequency receiver with accuracy of better than 50 cm and PPP with regional augmentation for instantaneous ambiguity resolution of 1–3 cm accuracy. We adapted the system for current COMPASS to provide PPP service. COMPASS observations from a regional network of nine stations are used for precise orbit determination and clock estimation in simulated real-time mode, the orbit and clock products are applied for real-time precise point positioning. The simulated real-time PPP service confirms that real-time positioning services of accuracy at dm-level and even cm-level is achievable with COMPASS only.     

An improved approach to model regional ionosphere and accelerate convergence for precise point positioning

Given the severe effects of the ionosphere on global navigation satellite system (GNSS) signals, single-frequency (SF) precise point positioning (PPP) users can only achieve decimeter-level positioning results. Ionosphere-free combinations can eliminate the majority of ionospheric delay, but increase observation noise and slow down dual-frequency (DF) PPP convergence. In this paper, we develop a regional ionosphere modeling and rapid convergence approach to improve SF PPP (SFPPP) accuracy and accelerate DF PPP (DFPPP) convergence speed. Instead of area model, ionospheric delay is modeled for each satellite to be used as a priori correction. With the ionospheric, wide-lane uncalibrated phase delay (UPD) and residuals satellite DCBs product, the wide-lane observations for DF users change to be high-precision pseudorange observations. The validation of a continuously operating reference station (CORS) network was analyzed. The experimental results confirm that the approach considerably improves the accuracy of SFPPP. For DF users, convergence time is substantially reduced.     

Evaluation of COMPASS ionospheric model in GNSS positioning

As important products of GNSS navigation message, ionospheric delay model parameters are broadcasted for single-frequency users to improve their positioning accuracy. GPS provides daily Klobuchar ionospheric model parameters based on geomagnetic reference frame, while the regional satellite navigation system of China’s COMPASS broadcasts an eight-parameter ionospheric model, COMPASS Ionospheric Model(CIM), which was generated by processing data from continuous monitoring stations, with updating the parameters every 2 h. To evaluate its performance, CIM predictions are compared to ionospheric delay measurements, along with GPS positioning accuracy comparisons. Real observed data analysis indicates that CIM provides higher correction precision in middle-latitude regions, but relatively lower correction precision for low-latitude regions where the ionosphere has much higher variability. CIM errors for some users show a common bias for in-coming COMPASS signals from different satellites, and hence ionospheric model errors are somehow translated into the receivers’ clock error estimation. In addition, the CIM from the China regional monitoring network are further evaluated for global ionospheric corrections. Results show that in the Northern Hemisphere areas including Asia, Europe and North America, the three-dimensional positioning accuracy using the CIM for ionospheric delay corrections is improved by 7.8%–35.3% when compared to GPS single-frequency positioning ionospheric delay corrections using the Klobuchar model. However, the positioning accuracy in the Southern Hemisphere is degraded due apparently to the lack of monitoring stations there.     

Ionospheric correction using GPS Klobuchar coefficients with an empirical night-time delay model

We proposed an ionospheric correction approach called NKlob to mitigate the ionospheric delay errors. NKlob is a modification of the original GPS Ionospheric Correction Algorithm (ICA), which uses an empirical night-time model depending on the time, geomagnetic location and periodicities of the ionospheric behavior to replace the night-time constant delay in GPS ICA. Performance of NKlob was evaluated by the independent total electron contents (TECs) derived from Global Ionospheric Maps (GIMs) of the International GNSS Services (IGS) and Jason-2 altimetry satellite during 2013–2017. Compared to GIM TECs, NKlob corrects 51.5% of the ionospheric delay errors, which outperforms GPS ICA by 6.3%. Compared to Jason-2 TECs, NKlob mitigates the ionospheric errors by 58.1%, which is approximately 3.7% better than that of GPS ICA. NKlob shows significant improvement in low-latitude and equatorial regions with respect to GPS ICA, meanwhile exhibiting comparable performance at middle and high latitudes. Since NKlob only requires slight technical changes at the processing level of GPS receivers, we suppose that it can be easily implemented for better ionospheric delay corrections of real-time GPS single-frequency applications.     

Mitigation of receiver biases in ionospheric observables from PPP with ambiguity resolution

PPP (Precise Point Positioning) is a GNSS (Global Navigation Satellite Systems) positioning method that requires SSR (State Space Representation) corrections in order to provide solutions with an accuracy of centimetric level. The so-called RT-PPP (Real-time PPP) is possible thanks to real-time precise SSR products, for orbits and clocks, provided by IGS (International GNSS Service) and its associate analysis centers such as CNES (Centre National d'Etudes Spatiales). CNES SSR products also enable RT-PPP with integer ambiguity resolution. In GNSS related literature, PPP with ambiguity resolution (PPP-AR) in real-time is often referred as PPP-RTK (PPP – Real Time Kinematic). PPP-WIZARD (PPP - With Integer and Zero-difference Ambiguity Resolution Demonstrator) is a software that is made available by CNES. This software is capable of performing PPP-RTK. It estimates slant ionospheric delays and other GNSS positioning parameters. Since ionospheric effects are spatially correlated by GNSS data from active networks, it is possible to model and provide ionospheric delays for any position in the network coverage area. The prior knowledge ionospheric delays can reduce positioning convergence for PPP-RTK users. Real-time ionospheric models could benefit from highly precise ionospheric delays estimated in PPP-AR. In this study, we demonstrate that ionospheric delays obtained throughout PPP-AR estimation are actu ally ionospheric observables. Ionospheric observables are biased by an order of few meters caused by the receiver hardware biases. These biases prohibit the use of PPP-WIZARD ionospheric delays to produce ionospheric models. Receiver biases correction is essential to provide ionospheric delays while using PPP-AR based ionospheric observables. In this contribution, a method was implemented to estimate and mitigate receiver hardware biases influence on slant ionospheric observables from PPP-AR. In order to assess the proposed approach, PPP-AR data from 12 GNSS stations were processed over a two-month period (March and April 2018). A comparison between IGS ionospheric products and PPP-AR based ionospheric observables corrected for receiver biases, resulted in a mean of differences of −39 cm and 51 cm standard deviation. The results are consistent with the accuracy of the IGS ionospheric products, 2–8 TECU, considering that 1 TECU is ~16 cm in L1. In another analysis, a comparison of ionospheric delays from 5 pairs of short baselines GNSS stations found an agreement of 0.001 m in mean differences with 22 cm standard deviation after receiver biases were corrected. Therefore, the proposed solution is promising and could produce high quality (1–2 TECU) slant ionospheric delays. This product can be used in a large variety of modeling approaches, since ionospheric delays after correction are unbiased. These results indicate that the proposed strategy is promising, and could benefit applications that require accuracy of 1–2 TECU (~16–32 cm in L1).     

基于空间统计方法的电离层折射修正技术

针对中国上空电离层所具有的特殊性和GPS观测站在中国西部分布相对稀疏的特点, 尝试探索中国卫星增强系统电离层时延信息修正技术, 为卫星导航定位以及遥感、遥测等空间应用工程的电波修正提供数据. 利用中国地壳形变监测网提供的双频GPS数据, 以空间统计方法为主要工具, 给出了普通Kriging电离层估计算法, 构建了平静期和磁暴期电离层理论变异模型, 详细分析了电离层折射修正的精度. 结果表明, 将空间统计方法应用于卫星增强系统中的电离层时延改正问题, 有利于提高增强系统的电离层折射修正精度, 特别是在观测样点相对较少的情况下, 有利于系统完整性的实现.      

GPS data processing of networks with mixed single- and dual-frequency receivers for deformation monitoring

In order to obtain crustal deformations of higher spatial resolution, existing GPS networks must be densified. This densification can be carried out using single-frequency receivers at moderate costs. However, ionospheric delay handling is required in the data processing. We adapt the Satellite-specific Epoch-differenced Ionospheric Delay model (SEID) for GPS networks with mixed single- and dual-frequency receivers. The SEID model is modified to utilize the observations from the three nearest dual-frequency reference stations in order to avoid contaminations from more remote stations. As data of only three stations are used, an efficient missing data constructing approach with polynomial fitting is implemented to minimize data losses. Data from large scale reference networks extended with single-frequency receivers can now be processed, based on the adapted SEID model. A new data processing scheme is developed in order to make use of existing GPS data processing software packages without any modifications. This processing scheme is evaluated using a sub-network of the German SAPOS network. The results verify that the new scheme provides an efficient way to densify existing GPS networks with single-frequency receivers.     

Near real-time PPP-based monitoring of the ionosphere using dual-frequency GPS/BDS/Galileo data

Ionosphere delay is very important to GNSS observations, since it is one of the main error sources which have to be mitigated even eliminated in order to determine reliable and precise positions. The ionosphere is a dispersive medium to radio signal, so the value of the group delay or phase advance of GNSS radio signal depends on the signal frequency. Ground-based GNSS stations have been used for ionosphere monitoring and modeling for a long time. In this paper we will introduce a novel approach suitable for single-receiver operation based on the precise point positioning (PPP) technique. One of the main characteristic is that only carrier-phase observations are used to avoid particular effects of pseudorange observations. The technique consists of introducing ionosphere ambiguity parameters obtained from PPP filter into the geometry-free combination of observations to estimate ionospheric delays. Observational data from stations that are capable of tracking the GPS/BDS/GALILEO from the International GNSS Service (IGS) Multi-GNSS Experiments (MGEX) network are processed. For the purpose of performance validation, ionospheric delays series derived from the novel approach are compared with the global ionospheric map (GIM) from Ionospheric Associate Analysis Centers (IAACs). The results are encouraging and offer potential solutions to the near real-time ionosphere monitoring.     

Ionospheric path delay models for spaceborne GPS receivers flying in formation with large baselines

GPS relative navigation filters could benefit notably from an accurate modeling of the ionospheric delays, especially over large baselines (>100 km) where double difference delays can be higher than several carrier wavelengths. This paper analyzes the capability of ionospheric path delay models proposed for spaceborne GPS receivers in predicting both zero-difference and double difference ionospheric delays. We specifically refer to relatively simple ionospheric models, which are suitable for real-time filtering schemes. Specifically, two ionospheric delay models are evaluated, one assuming an isotropic electron density and the other considering the effect on the electron density of the Sun aspect angle. The prediction capability of these models is investigated by comparing predicted ionospheric delays with measured ones on real flight data from the Gravity Recovery and Climate Experiment mission, in which two satellites fly separated of more than 200 km. Results demonstrate that both models exhibit a correlation in the excess of 80% between predicted and measured double-difference ionospheric delays. Despite its higher simplicity, the isotropic model performs better than the model including the Sun effect, being able to predict double differenced delays with accuracy smaller than the carrier wavelength in most cases. The model is thus fit for supporting integer ambiguity fixing in real-time filters for relative navigation over large baselines. Concerning zero-difference ionospheric delays, results demonstrate that delays predicted by the isotropic model are highly correlated (around 90%) with those estimated using GPS measurements. However, the difference between predicted and measured delays has a root mean square error in the excess of 30 cm. Thus, the zero-difference ionospheric delays model is not likely to be an alternative to methods exploiting carrier-phase observables for cancelling out the ionosphere contribution in single-frequency absolute navigation filters.     

Ionospheric climate index as a driving parameter for the NeQuick model

Ionospheric delay is one of the significant error sources for global navigation satellite system (GNSS) positioning. GNSSs broadcast the coefficients of the ionospheric model to correct ionospheric delay for single-frequency users. A modified three-dimensional model (NeQuick G) based on the NeQuick climatological model is adopted for Galileo users. The NeQuick G model uses the effective ionization level (Az) instead of the sunspot number as the driving parameter. In this study, we introduce the ionospheric climate index (ICI) as a new driving parameter for the NeQuick model. In comparison, the ICI-driven NeQuick model has a better performance than the Az-driven NeQuick G model at both low and high latitudes. In addition, only one GNSS station at low latitudes is required to calculate the ICI, which would save maintenance costs and improve the efficiency of updating the broadcast coefficients. This model has potential application value for future upgrades of Galileo’s ionospheric broadcast model.     

观测站稀疏地区的WAAS电离层时延网格修正算法

在改进的广域增强系统电离层时延网格算法的基础上，给出了针对观测量比较少的地区比较适用的电离层时延网格修正算法，并通过模拟数据和GPS实测数据与原方法进行了分析比较．结果表明，在观测站稀疏的情况下，本文的计算方法模式的精度比原方法有较大的提高．     

An annual variation analysis of the ionospheric spatial gradient over a regional area for GNSS applications

An ionospheric spatial gradient represents the ionosphere delay difference between different locations, and its variation over a specific area is important for implementing differential GNSS systems. An estimation method for the ionospheric spatial gradient over a small regional area is proposed. A plate map model is implemented for the direct estimation of the gradients. Nine years of GPS data were processed to figure out the annual variation of the mean gradient at the mid-geomagnetic latitude of 30° N. Gradients along the north–south direction have a mean of 0.65 mm/km and follow solar-cycle variations.     

电离层效应的测时误差及其修正

电磁波经过电离层传播时会受到电离层折射的影响而产生延迟, 星载接收机探测到的时间是信号延迟之后的到达时间. 某次实验数据显示, 一些波段的瞬态电测辐射信号的群时延之差可达105ns数量级, 这在对信号源进行时差定位时是不能直接运用的. 为有效消除电离层延迟的影响, 将双频修正法应用于某项工程中, 利用接收到的实验数据求解出电离层的TEC(电离层总电子含量), 并在此基础上对信号到达星载接收机的时间进行修正. 最后,对修正结果进行了验证, 给出了误差来源.      

一种基于系数择优的低阶球谐电离层延迟改正模型

针对单频接收机的电离层延迟改正问题, 提出了一种基于系数择优的低阶球谐电离层延迟改正模型. 按照电离层延迟改正模型参数择优问题的描述, 明确参数优化的目标和约束条件, 根据参数选择可编码的特点, 提出了利用遗传算法进行参数择优的方法及步骤. 以欧洲定轨中心(CODE)提供的电离层数据作为参考标准, 对参数择优模型、 低阶球谐模型和Klobuchar模型模拟的区域电离层VTEC精度进行了比较分析. 结果表明, 较之相同系数个数的低阶球谐模型, 参数择优模型精度平均改进了1～2TECU, 而且比Klobuchar模型及低阶球谐模型能更好地反映电离层的周日变化及纬度变化特征.      

实时电离层格网数据精度评估

电离层延迟是制约单频接收机定位精度的重要误差源之一.为提高单频接收机的实时电离层改正精度,需要实时电离层数据.以中国科学院空天信息创新研究院提供的实时电离层数据为例,对比分析不同太阳活动期实时电离层数据及预报电离层数据与IGS最终电离层数据之间的差值以及不同太阳活动期、不同纬度测站的电离层数据对电离层延迟进行改正后得到的定位精度.结果表明:在低太阳活动期和高太阳活动期,实时电离层数据无法很好地反映大部分海洋上空的电离层变化特性;对不同太阳活动期,实时电离层数据在高纬度测站的定位精度优于预报数据和广播模型,在中纬度测站的定位精度略低于预报数据而与广播模型定位精度相当,在低纬度测站的定位精度略优于预报数据和广播模型.      

The use of ionospheric tomography and elevation masks to reduce the overall error in single-frequency GPS timing applications

Signals from Global Positioning System (GPS) satellites at the horizon or at low elevations are often excluded from a GPS solution because they experience considerable ionospheric delays and multipath effects. Their exclusion can degrade the overall satellite geometry for the calculations, resulting in greater errors; an effect known as the Dilution of Precision (DOP). In contrast, signals from high elevation satellites experience less ionospheric delays and multipath effects. The aim is to find a balance in the choice of elevation mask, to reduce the propagation delays and multipath whilst maintaining good satellite geometry, and to use tomography to correct for the ionosphere and thus improve single-frequency GPS timing accuracy. GPS data, collected from a global network of dual-frequency GPS receivers, have been used to produce four GPS timing solutions, each with a different ionospheric compensation technique. One solution uses a 4D tomographic algorithm, Multi-Instrument Data Analysis System (MIDAS), to compensate for the ionospheric delay. Maps of ionospheric electron density are produced and used to correct the single-frequency pseudorange observations. This method is compared to a dual-frequency solution and two other single-frequency solutions: one does not include any ionospheric compensation and the other uses the broadcast Klobuchar model. Data from the solar maximum year 2002 and October 2003 have been investigated to display results when the ionospheric delays are large and variable. The study focuses on Europe and results are produced for the chosen test site, VILL (Villafranca, Spain). The effects of excluding all of the GPS satellites below various elevation masks, ranging from 5° to 40°, on timing solutions for fixed (static) and mobile (moving) situations are presented. The greatest timing accuracies when using the fixed GPS receiver technique are obtained by using a 40° mask, rather than a 5° mask. The mobile GPS timing solutions are most accurate when satellites at lower elevations continue to be included: using a mask between 10° and 20°. MIDAS offers the most accurate and least variable single-frequency timing solution and accuracies to within 10 ns are achieved for fixed GPS receiver situations. Future improvements are anticipated by combining both GPS and Galileo data towards computing a timing solution.     

Performance evaluation of IRI-2007 at equatorial latitudes and its Matlab version for GNSS applications

International Reference Ionosphere (IRI) model is the widely used empirical model for ionospheric predictions, especially TEC which is an important parameter for radio navigation and communication. The Fortran based IRI-2007 does not support real-time interactive visualization and debugging. Therefore, the source code is converted into Matlab and is validated for the purposes of this study. This facilitates easy representation of results and for near real-time implementation of IRI in the applications including spacecraft launching, now casting, pseudolite based navigation systems etc. In addition, the vertical delay results over the equatorial region derived from IRI and GPS data of three IGS stations namely Libreville (Garbon, Africa), Brasilia (Brazil, South America) and Hyderabad (India, Asia) are compared. As the IRI model does not account for plasmasphere TEC, the vertical delays are underestimated compared to vertical delays of GPS signals. Therefore, the model should be modified accordingly for precise TEC estimation.     

基于北斗GEO卫星双频观测值连续监测电离层延迟

利用北斗GEO卫星观测数据直接计算电离层延迟。由于GEO卫星具有固定穿刺点和静地的特性,使得观测站监测电离层变化时可不考虑空间变化,并可进行连续不间断监测。通过分析北斗GEO卫星三种频率码伪距和载波相位观测值不同组合,选取B1&B2双频计算电离层延迟为最优组合,采用相位平滑伪距的方法计算电离层延迟TEC,相较其他电离层模型,该方法的优点是不会引入模型误差,可得到连续的高精度的电离层延迟监测结果。     

Time delay of ionospheric TEC storms to geomagnetic storms and pre-storm disturbance events in East Asia

Using the TEC data at Beijing (39.61°N, 115.89°E)/Yakutsk (62.03°N, 129.68°E) stations of East Asia regions and relevant geomagnetic data from 2010 to 2017, we have studied the time delay of ionospheric storms to geomagnetic storms and compare it with our previous results of Taoyuan (25.02°N, 121.21°E) station (Zhang et al., 2020). The data shows a well-known local time dependence of the time delay, and seasonal dependences are different at these stations. In addition, there is no correlation between the time delay and the magnetic storm intensity /solar activity, except the time delay of negative storms has weakly negative dependence on the solar activity. Comparing with the results of Taoyuan station which is located at EIA region in East Asia, we find that the time delay increases nonlinearly as the latitude decreases due to different ionospheric backgrounds at these places. Moreover, the pre-storm disturbance events are found to have similar statistical characteristics as the pre-storm enhancement in Europe middle latitudes (Bure?ová and La?tovi?ka, 2007). By subtracting the common features of the pre-storm disturbance events, we preliminarily infer that auroral activity might be main driver of the pre-storm disturbance events.