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.     

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.      

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.     

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.     

NeQuick G model based scale factor determination for using SBAS ionosphere corrections at low earth orbit

A space-based augmentation system (SBAS) provides real-time correction data for global navigation satellite system (GNSS) users near ground. In order to use the SBAS ionosphere correction for low Earth orbit (LEO) satellites, the correction should be scaled down for the LEO altitude. This scale factor varies with ionosphere distribution and it is hard to determine the value at LEO in real time. We propose a real-time scale factor determination method by using Galileo GNSS’s NeQuick G model. A LEO satellite GPS data and SBAS data received on ground were used to evaluate the performance of the NeQuick G derived variable scale factor. The NeQuick G derived scale factor shows a significant accuracy improvement over NeQuick G model or pre-determined constant scale factor. It improves a vertical positioning accuracy of the LEO satellite. The error mean reductions of the vertical positioning over NeQuick G and the constant scale factor are 31.5% and 11.7%, respectively.     

基于极大验后推估理论的全球电离层地图预报

提出了一种基于极大验后估计理论的全球电离层预报方法，基于中国科学院电离层分析中心（CAS）提供的快速全球电离层地图（GIM），实现了1天、2天和5天GIM的预报。以国际GNSS服务组织（IGS）最终GIM、Jason测高卫星提供的电离层观测信息及全球GNSS基准站实测电离层总电子含量（TEC）为基准，评估了2008－2017年CAS电离层预报GIM在全球大陆及海洋区域的精度，并与欧洲定轨中心（CODE）、欧洲空间局（ESA）和西班牙加泰罗尼亚理工大学（UPC）的预报GIM进行对比。在评估时段内，与IGS-GIM相比，CAS预报GIM精度为2.4~3.1 TECU；与测高卫星TEC相比，CAS预报GIM的精度为5.1~6.6 TECU；与全球基准站实测TEC相比，CAS预报GIM的电离层延迟修正精度优于80%。总体来看，CAS预报GIM与CODE预报GIM精度相当，显著优于ESA和UPC预报GIM。      

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.      

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.     

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.     

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.     

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.     

Ionosphere modelling for Galileo single frequency users: Illustration of the combination of the NeQuick model and GNSS data ingestion

The ionospheric effect remains one of the main factors limiting the accuracy of Global Navigation Satellite Systems (GNSS) including Galileo. For single frequency users, this contribution to the error budget will be mitigated by an algorithm based on the NeQuick global ionospheric model. This quick-run empirical model provides flexible solutions for combining ionospheric information obtained from various sources, from GNSS to ionosondes and topside sounders. Hence it constitutes an interesting simulation tool not only serving Galileo needs for mitigation of the ionospheric effect but also widening the use of new data.     

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.     

南极GPS定位中的电离层延迟分析

基于南极地区国际GNSS服务组织(IGS,International GNSS Service)跟踪站的全球定位系统(GPS,Global Position System)双频实测数据,分析了南极地区电离层延迟的变化情况及其二阶项延迟对南极GPS定位结果的影响.结果表明:南极地区的总电子含量(TEC,Total Electron Content)日间波动频繁,其日间TEC最大值变化较中纬度地区剧烈;在南极地区夏季,电离层二阶项延迟对GPS定位结果的影响可达cm级.同时,由于欧洲定轨中心(CODE,The European Center for Orbit Determination)提供的全球电离层模型(GIM,Global Ionosphere Maps)在南极区域应用的局限性,通过选取南极地区6个IGS跟踪站作为基准站建立了区域电离层TEC模型(RIM,Regional Ionosphere Model).经实测数据计算证明,对于南极地区,RIM的定位精度在一定程度上优于全球电离层模型GIM.     

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...     

GPS phase difference variation statistics: A comparison between phase scintillation index and proxy indices

Scintillated GPS phase observations are traditionally characterized by the phase scintillation index, derived from specialized GPS receivers usually tracking at 50 Hz. Geodetic quality GPS receivers, on the other hand, are normally tracking at frequencies up to 1 Hz. However, availability of continuously operating geodetic receivers both in time and geographical location are superior to scintillation receiver’s coverage in many parts of the world. This motivates scintillation studies using regional and global geodetic GPS networks. Previous studies have shown the usefulness of GPS estimated total electron content variations for detecting ionospheric irregularities. In this paper, collocated geodetic and scintillation receivers are employed to compare proxy indices derived from geodetic receivers with the phase scintillation index during quiet and moderately disturbed ionospheric conditions. Sensitivity of the phase scintillation indices at high latitude stations to geomagnetic activity is discussed. Global mapping of ionospheric disturbances using proxy indices from real-time 1 Hz GPS stations are also presented.     

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.     

基于CIT技术的广域增强系统电离层延迟修正算法

提出了一种基于电离层层析成像(CIT)技术的广域增强系统(WAAS)电离层延迟 修正算法. 该算法利用模式基函数与截断奇异值分解正则化组合的方式, 实现WAAS单频用户的电离层延迟误差修正. 基于中国区域23个广域基准站 和10个用户站的仿真结果分析表明, 传统的网格算法和基于CIT技术的电离 层延迟修正算法的电离层延迟修正精度与太阳活动、昼夜变化及地磁纬度 之间均存在明显的相关性. 基于CIT技术的电离层延迟修正算法精度优于网格算法, CIT算法的平均误差与标准差相比网格算法均有较大幅度的下降.      

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.     

基于双频GPS观测的电离层TEC与硬件延迟反演方法

利用全球定位系统（Global Positioning System,GPS）的双频观测数据反演得到电离层的总电子含量（Total Electron Content,TEC）,使得广域甚至全球范围高时空分辨率的电离层观测研究成为可能,但由于GPS卫星和接收机对信号的硬件延迟可导致TEC测量系统偏差,因此,需要探索反演TEC并估测GPS卫星与接收机硬件延迟的有效算法.本文根据电离层电波传播理论,阐述了基于双频GPS观测提取电离层TEC的方法,给出TEC与硬件延迟的基本关系.综合研究了TEC与硬件延迟的反演方法,进行分析与归纳分类,在此基础上提出了有待深入研究的问题.