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.     

Calibration errors in determining slant Total Electron Content (TEC) from multi-GNSS data

The global navigation satellite system (GNSS) is presently a powerful tool for sensing the Earth's ionosphere. For this purpose, the ionospheric measurements (IMs), which are by definition slant total electron content biased by satellite and receiver differential code biases (DCBs), need to be first extracted from GNSS data and then used as inputs for further ionospheric representations such as tomography. By using the customary phase-to-code leveling procedure, this research comparatively evaluates the calibration errors on experimental IMs obtained from three GNSS, namely the US Global Positioning System (GPS), the Chinese BeiDou Navigation Satellite System (BDS), and the European Galileo. On the basis of ten days of dual-frequency, triple-GNSS observations collected from eight co-located ground receivers that independently form short-baselines and zero-baselines, the IMs are determined for each receiver for all tracked satellites and then for each satellite differenced for each baseline to evaluate their calibration errors. As first derived from the short-baseline analysis, the effects of calibration errors on IMs range, in total electron content units, from 1.58 to 2.16, 0.70 to 1.87, and 1.13 to 1.56 for GPS, Galileo, and BDS, respectively. Additionally, for short-baseline experiment, it is shown that the code multipath effect accounts for their main budget. Sidereal periodicity is found in single-differenced (SD) IMs for GPS and BDS geostationary satellites, and the correlation of SD IMs over two consecutive days achieves the maximum value when the time tag is around 4?min. Moreover, as byproducts of zero-baseline analysis, daily between-receiver DCBs for GPS are subject to more significant intra-day variations than those for BDS and Galileo.     

GNSS电离层模型改正精度评估与分析

电离层时延误差是导航定位信号在空间传播路径上的主要误差源之一,因此全面了解GNSS电离层模型的改正精度具有一定现实意义.根据GPS,BDS和Galileo系统所采用的电离层修正模型,利用2014年电离层校正参数,以高精度全球电离层图为基准,评估分析了三大系统电离层时延的改正精度.结果表明:目前GNSS使用的几种电离层修正模型的改正率在65~75%左右;Galileo系统使用的第二版NeQuick模型与第一版NeQuick模型相比在修正精度上并无显著提高;GPS使用的Klobuchar 8参数模型在北半球25°-45°N的中纬度地区精度很高,但是在全球其他区域精度较低,分布性较差,而NeQuick模型全球改正率分布则较为平均且平滑.      

The ionosphere,radio navigation,and global navigation satellite systems

This article is a review of Global Navigation Satellite Systems (GNSS) for space scientists who are interested in how GNSS signals and observables can be used to understand ionospheric dynamics and, conversely, how ionospheric dynamics affect the operational capabilities of GNSS receivers. The most common form of GNSS is the Global Positioning System (GPS); we will first review its operating principles and then present a discussion of errors, of which ionospheric propagation is the most significant. Methods and systems for mitigating errors will be introduced, along with a discussion of modernization plans for GPS and for entirely new systems such as Galileo. In the second half of this article the effects of the ionosphere on GPS signals will be examined in more detail, particularly ionospheric propagation, leading to a discussion of the relation of TEC to ranging errors. Next, the subject of scintillations will also be introduced and connected to the presence and scale sizes of irregularities. Scintillations will be examined as spatial and temporal structures. The method of measuring scintillation pattern drift and ionospheric velocity will be discussed. We conclude by examining ionospheric effects on GPS at midlatitudes.     

On the importance of total electron content enhancements during the extreme solar minimum

Observations of ionospheric vertical total electron content (vTEC) from European ground-based Global Navigation Satellite Systems (GNSS) receivers during the period January 2008–January 2010 are used to investigate, for the first time, vTEC sensitivity to weak geomagnetic disturbances under extreme solar minimum conditions. This study shows a significant number of events for the period in question, all of which exhibited some form of exceptionally large values of vTEC during small-magnitude geomagnetic disturbances. To illustrate our point on the importance of vTEC enhancements during the extreme solar minimum and its relevance for the current GNSS and future Galileo applications, we present in this paper the results associated with two significant events that both occurred in equinoctial months. The 10–12 October 2009 event of anomalous TEC enhancement at two distant mid-latitude locations HERS (0.3 E; 50.9 N) and NICO (33.4 E, 35.1 N) is discussed in the context of strong vTEC variations during the well established ionospheric storm on 11 October 2008. We conclude with a short summary of the new findings and their consequences on ionospheric monitoring and modelling for operational communication and navigation systems.     

Galileo卫星导航系统广播Nequick模型及其参数拟合

提出了基于IGRF模型的Galileo广播Nequick模型及其参数拟合算法, 解决了Galileo信号仿真中地理场景映射与地磁坐标下的电离层延时修正参数拟合问题. 应用IGRF模型, 可计算出任意给定位置和时间点的地磁参数以及E层、 F₁层、F₂层的电子密度, 从而计算出Galileo电离层修正参数. 仿真结果表明, 该算法拟合的全球电离层延时与IGS提供的实际观测值基本一致, 仿真精度高于一般的经验电离层模型, 实现了Galileo卫星信号的电离层延时修正参数的精确仿真.      

Assessment of the NeQuick model at mid-latitudes using GNSS TEC and ionosonde data

The modelling of the total electron content (TEC) plays an important role in global navigation satellite systems (GNSS) accuracy, especially for single-frequency receivers, the most common ones constituting the mass market. For the latter and in the framework of Galileo, the NeQuick model has been chosen for correcting the ionospheric error contribution and will be integrated into a global algorithm providing the users with daily updated information.     

The multi-source data fusion global ionospheric modeling software—IonoGim

We introduce a new global ionospheric modeling software—IonoGim, using ground-based GNSS data, the altimetry satellite and LEO (Low Earth Orbit) occultation data to establish the global ionospheric model. The software is programmed by C++ with fast computing speed and highly automatic degree, it is especially suitable for automatic ionosphere modeling. The global ionospheric model and DCBs obtained from IonoGim were compared with the CODE (Center for Orbit Determination in Europe) to verify its accuracy and reliability. The results show that IonoGim and CODE have good agreement with small difference, indicating that IonoGim owns high accuracy and reliability, and can be fully applicable for high-precision ionospheric research. In addition, through comparison between only using ground-based GNSS observations and multi-source data model, it can be demonstrated that the space-based ionospheric data effectively improve the model precision in marine areas where the ground-based GNSS tracking station lacks.     

GNSS single frequency ionospheric range delay corrections: NeQuick data ingestion technique

A study of the performance of the NeQuick model and the Klobuchar model for GNSS single frequency range delay correction on a global scale was done using data for moderate solar activity. In this study NeQuick was used in the way intended for Galileo. This study is to assess the performance of the two models at each ionospheric geographic region during moderate solar activity as previously published studies were concentrated only on high solar activity. The results obtained showed that NeQuick outperformed Klobuchar for the whole year at the three geographical regions of the ionosphere. In terms of monthly root mean square of mismodeling, NeQuick outperformed Klobuchar by 15 TECU or more at low-latitudes, 5 TEC or more at mid-latitudes, and 1 TECU or more at high-latitudes.     

Using TensorFlow-based Neural Network to estimate GNSS single frequency ionospheric delay (IONONet)

In the last 20?years, and in particular in the last decade, the availability of propagation data for GNSS has increased substantially. In this sense, the ionosphere has been sounded with a large number of receivers that provide an enormous amount of ionospheric data. Moreover, the maturity of the models has also been increased in the same period of time. As an example, IGS has ionospheric maps from GNSS data back to 1998, which would allow for the correlation of these data with other quantities relevant for the user and space weather (such as Solar Flux and Kp). These large datasets would account for almost half a billion points to be analyzed. With the advent and explosion of Big Data algorithms to analyze large databases and find correlations with different kinds of data, and the availability of open source code libraries (for example, the TensorFlow libraries from Google that are used in this paper), the possibility of merging these two worlds has been widely opened. In this paper, a proof of concept for a single frequency correction algorithm based in GNSS GIM vTEC and Fully Connected Neural Networks is provided. Different Neural Network architectures have been tested, including shallow (one hidden layer) and deep (up to five hidden layers) Neural Network models. The error in training data of such models ranges from 50% to 1% depending on the architecture used. Moreover, it is shown that by adjusting a Neural Network with data from 2005 to 2009 but tested with data from 2016 to 2017, Neural Network models could be suitable for the forecast of vTEC for single frequency users. The results indicate that this kind of model can be used in combination with the Galileo Signal-in-Space (SiS) NeQuick G parameters. This combination provides a broadcast model with equivalent performances to NeQuick G and better than GPS ICA for the years 2016 and 2017, showing a 3D position Root Mean Squared (RMS) error of approximately 2?m.     

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).     

Characterisation of residual ionospheric errors in bending angles using GNSS RO end-to-end simulations

Global Navigation Satellite System (GNSS) radio occultation (RO) is an innovative meteorological remote sensing technique for measuring atmospheric parameters such as refractivity, temperature, water vapour and pressure for the improvement of numerical weather prediction (NWP) and global climate monitoring (GCM). GNSS RO has many unique characteristics including global coverage, long-term stability of observations, as well as high accuracy and high vertical resolution of the derived atmospheric profiles. One of the main error sources in GNSS RO observations that significantly affect the accuracy of the derived atmospheric parameters in the stratosphere is the ionospheric error. In order to mitigate the effect of this error, the linear ionospheric correction approach for dual-frequency GNSS RO observations is commonly used. However, the residual ionospheric errors (RIEs) can be still significant, especially when large ionospheric disturbances occur and prevail such as during the periods of active space weather. In this study, the RIEs were investigated under different local time, propagation direction and solar activity conditions and their effects on RO bending angles are characterised using end-to-end simulations. A three-step simulation study was designed to investigate the characteristics of the RIEs through comparing the bending angles with and without the effects of the RIEs. This research forms an important step forward in improving the accuracy of the atmospheric profiles derived from the GNSS RO technique.     

Klobuchar电离层模型误差分析及预测

电离层延迟误差是全球导航卫星系统(global navigation satellite system,GNSS)中的重要误差源之一.目前在电离层延迟改正模型中,应用最广泛的是Klobuchar参数模型,但是该模型的改正率仅能达到60％左右,无法满足日益增长的精度需求.将国际GNSS监测评估系统(internation...     

45°(N)纬度带的Klobuchar like电离层延迟季节修正模型与评估

电离层延迟是全球卫星导航系统（GNSS）的主要误差源之一。对于装配GNSS单频接收机的航空器,选择简单有效的Klobuchar广播电离层模型来改正电离层延迟误差,其修正率为50%～60%。针对45°（N）纬度带,提出了更高电离层修正需求。考虑到季节因素对中高纬度地区电离层的显著影响,利用GIMs（Global Ionospheric Maps）分析了昼夜中TEC（Total Electron Content）的峰值和谷值随季节（年积日）的变化,建立了一种适用于45°（N）纬度带的Klobuchar like电离层模型。该模型不增加广播模型系数,新模型的夜间和VTEC高峰时电离层修正率分别达到了82%和80%,表明在穿刺点集中的45°(N)纬度地区使用该模型可以更精确地描述该地区的电离层,帮助航空器实现更高精度的定位。     

The adjusted optical properties for Galileo/BeiDou-2/QZS-1 satellites and initial results on BeiDou-3e and QZS-2 satellites

Solar Radiation Pressure (SRP) is the dominant non-gravitational perturbation for GNSS (Global Navigation Satellite System) satellites. In the absence of precise surface models, the Empirical CODE Orbit Models (ECOM, ECOM2) are widely used in GNSS satellite orbit determination. Based on previous studies, the use of an a priori box-wing model enhances the ECOM model, especially if the spacecraft is a stretched body satellite. However, so far not all the GNSS system providers have published their metadata. To ensure a precise use of the a priori box-wing model, we estimate the optical parameters of all the Galileo, BeiDou-2, and QZS-1 (Quasi Zenith Satellite System) satellites based on the physical processes from SRP to acceleration. Validation using orbit prediction proves that the adjusted parameters of Galileo and QZS-1 satellites exhibit almost the same performance as the corresponding published and “best guess” values. Whereas, the estimated parameters of BeiDou-2 satellites demonstrate an improvement of more than 60% over the initial “guess” values. The resulting optical parameters of all the satellites are introduced into an a priori box-wing model, which is jointly used with ECOM and ECOM2 model in the orbit determination. Results show that the pure ECOM2 model exhibits better performance than the pure ECOM model for Galileo, BeiDou-2 GEO and QZS-1 orbits. Combined with the a priori box-wing model the ECOM model (ECOM+BW) results in the best Galileo, BeiDou-2 GEO and QZS-1 orbits. The standard deviation (STD) of satellite laser ranging residuals reduce by about 20% and 5% with respect to the pure ECOM2 model for Galileo and BeiDou-2 GEO orbits, while the reductions are about 40% and 60% for QZS-1 orbits in yaw-steering and orbit-normal mode respectively. BeiDou-2 IGSO and MEO satellite orbits do not benefit much from the a priori box-wing model. In summary, we suggest setting up a unified SRP model of ECOM+BW for Galileo, QZS-1, and BeiDou-2 orbits based on the adjusted metadata. In addition, we estimate the optical parameters of BeiDou-3e and QZS-2 satellites using a limited number of tracking stations. Results regarding the unified SRP model indicate the same advantages, the STD of satellite laser ranging residuals reduces by about 30% and 20% for QZS-2 and BeiDou-3e orbits respectively over orbit products without a priori model. The estimation procedure is effective and easy to apply to the new emerging satellites in the future.     

软件GNSS信号模拟器架构与中频信号生成

软件GNSS(Global Navigation Satellite Systems)信号模拟器对于GNSS接收机的高效研发将做出重要贡献,因其结构灵活、开放性以及低成本.以GPS/Galileo组合系统为例,讨论了软件GNSS中频信号模拟器的架构,主要功能模块包括卫星星座仿真、接收机轨迹生成、传播通道特性仿真(包括电离层模型、对流层模型、多径模型等)、数字中频信号生成.在此基础上,着重阐述了数字中频信号生成模块的实现,功率谱图及分析结果验证了所生成的信号,包括GPS L1 C/A,Galileo E1 CBOC(Composite Binary Offset Carrier),Galileo E5a和E5b信号.     

一种用于电离层TEC监测的GNSS信号载波跟踪算法

全球卫星导航系统（GNSS）是电离层TEC监测中应用最普遍的手段. 目前方法通常是在传统导航用途的GNSS接收机输出的原始观测量基础上,经过数据后处理得到电离层TEC信息,其GNSS信号的跟踪处理算法依然采用GNSS导航接收机的算法. 针对GNSS系统用于电离层TEC监测的特殊性,提出一种称为GNSS双频信号和差联合跟踪的新算法,与传统方法相比,该算法直接跟踪电离层TEC的变化,可以提高电离层TEC跟踪的灵敏度和TEC的观测精度,改善电离层TEC监测性能.      

Refinement of global ionospheric coefficients for GNSS applications: Methodology and results

We developed the methodology for the optimal estimation of global ionospheric coefficients of the current Global Navigation Satellite Systems (GNSSs), including the eight- and ten-parameter Klobuchar-like as well as NeQuick models. The ionospheric coefficients of those correction models are calculated from two sets of globally distributed tracking stations of the International GNSS Services (IGS). Performance of the re-estimated Klobuchar-like and NeQuick coefficients are validated during 2002–2014 over the continental and oceanic areas, respectively. Over the continental areas, GPS TECs derived from 40 ground GPS receivers are selected as reference. The eight-, ten-parameter Klobuchar-like and NeQuick models can mitigate the ionospheric delay by 65.8, 67.3 and 75.0%, respectively. Over the global oceans, the independent TECs derived from Jason-1&2 altimeters are used as reference. The re-estimated ionospheric correction models can mitigate 56.1–66.7% of the delay errors. Compared to the original GPS Ionospheric Correction Algorithm (ICA), performance of those eight-, ten-parameter Klobuchar-like and NeQuick models has improved 3.4, 5.9 and 13.4% during the whole test period, respectively. The methodology developed here takes the advantage of high-quality ionospheric TECs derived from the global network of GNSS receivers. The re-estimated ionospheric coefficients can be used as precise ionospheric products to monitor and assess GNSS broadcast ionospheric parameters and to improve the performance of various single-frequency GNSS applications.     

基于NTCM-BC模型的全球卫星导航系统单频电离层延迟修正

选择NTCM-BC模型作为单频电离层延迟修正模型,通过非线性最小二乘拟合的方法,利用提前一天预测的电离层图（COPG文件）,计算得到NTCM-BC模型修正系数;利用Klobuchar模型和IGS发布的GIM数据对NTCM-BC模型进行比较和分析.对太阳活动高、中、低年实测数据的分析结果表明:全球平均水平上,NTCM-BC模型的电离层延迟修正性能明显优于Klobuchar模型,NTCM-BC模型的TEC平均误差和均方根误差比Klobuchar模型分别下降了41%和30%;模型的TEC计算误差与太阳活动剧烈程度成正相关,即太阳活动高年模型误差较大,太阳活动低年误差相对较低.相较于磁静日,磁扰日期间Klobuchar模型和NCTM模型的误差均有一定程度的增加.此外,模型的电离层修正误差同时存在明显的纬度、季节和地方时差异.      

NeQuick2 validation using multi-satellite and ground data

Global Navigation Satellite System’s (GNSS) positioning calculation is prone to ionospheric errors. Single frequency GNSS users receive ionospheric corrections through broadcast ionospheric models. Therefore, the accuracy of ionospheric models must be validated based on various geographic and geomagnetic conditions. In this work, an attempt is made to validate NeQuick2 electron density (Ne) using multiple sources of space-based and ground-based data at the Arabian Peninsula and for low solar activity conditions. These sources include space-based data from Swarm, DMSP and COSMIC-2 satellite constellations and ground-based data from GNSS receiver and the ionosonde. The period of this study is 1 year from October 2019 to September 2020. Analysis shows that the agreement between NeQuick2 and experimental Ne close to the peak density height depends on seasons and time of the day with the largest errors found in Autumn and during the daytime. NeQuick2 generally overestimates Ne during the daytime. During the early morning and evening hours, Ne estimates seem to be fairly accurate with slight underestimation in Winter and Spring. Estimation of slab thickness by NeQuick2 is found to be close to the values calculated using collocated ionosonde and GNSS receiver.