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。      

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.     

Galileo real-time orbit determination with multi-frequency raw observations

Real-time GNSS-based applications require corresponding real-time orbit products. While traditional GNSS orbits are generated with the dual-frequency IF (Ionosphere-Free) model, the increase of multi-frequency signal satellites brings new challenges for the data processing. Therefore, real-time orbit determination with the multi-frequency UC (Uncombined) model is introduced in this study considering its flexibility. With the derived mathematical model conforming to IGS (International GNSS Service) dual-frequency clock definition and one-week triple-frequency Galileo observation data from 90 IGS network stations, the convergence and accuracy of real-time orbits is assessed and the characteristics of satellite IFCB (Inter-Frequency Clock Bias) are analyzed. Results indicate that the model differences, including dual-frequency IF model, dual-frequency UC model and triple-frequency UC model, contribute to only cm-level differences with CODE (Center for Orbit Determination in Europe) final orbits after a convergence time of around 12 h. The constellation-mean RMS (Root Mean Square) differences of the converged real-time orbits with the CODE final orbits reaches about 5.0 cm, 7.0 cm and 5.0 cm for the radial, tangential and normal directions. The convergence of satellite IFCB is much faster than that of satellite orbit, which reflects a loose correlation between these two parameters. While the Galileo satellite IFCB are temporally stable, the modeling of satellite IFCB may be unreliable when over constrained and becomes even more unstable with commonly encountered datum changes. In summary, real-time GNSS orbit determination with multi-frequency raw observations is feasible and extendable with proper treatment of IFCB.     

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...     

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.     

风云三号C星GNOS北斗掩星电离层探测初步结果

利用风云三号卫星C星GNOS掩星探测仪电离层数据,分析了2013年10月FY-3C GNOS探测的北斗掩星电离层廓线分布,将2013年10月1日至2015年10月10日期间FY-3C GNOS观测的F₂层峰值电子密度（N_mF₂）与地面电离层测高仪观测结果进行对比,验证了FY-3C GNOS北斗电离层掩星的探测精度.结果表明,FY3-C GNOS北斗电离层掩星与电离层测高仪探测的N_mF₂数据相关系数为0.96,平均偏差为10.21%,标准差为19.61%.在不同情况下其数据精度有如下特征:白天精度高于夜晚;夏季精度高于分季,分季精度高于冬季;中纬地区精度高于低纬地区,低纬地区精度高于高纬地区; BDS倾斜同步轨道（IGSO）卫星精度高于同步轨道（GEO）卫星和中轨道（MEO）卫星.FY-3C GNOS北斗电离层掩星与国际上其他掩星电离层数据精度的一致性对GNSS掩星探测资料的综合利用具有重大意义.      

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).     

Kalman滤波估算电离层延迟的一种优化方法

频间偏差(Inter Frequency Bias,IFB)通常会给电离层延迟的解算带来误差.目前从电离层延迟中消除频间偏差的方法是基于GPS双频观测数据建立垂直电离层模型,利用卡尔曼滤波实时估算电离层模型系数和频间偏差.然而滤波过程中的测量噪声协方差矩阵没有考虑系统观测量之间的相关性,这会导致滤波模型不准确,进而影响...     

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.     

Eliminating negative VTEC in global ionosphere maps using inequality-constrained least squares

Currently, ground-based Global Navigation Satellite System (GNSS) stations of the International GNSS Service (IGS) are distributed unevenly around the world. Most of them are located on the mainland, while only a small part of them are scattered on some islands in the oceans. As a consequence, many unreasonable zero values (in fact negative values) appear in Vertical Total Electron Content (VTEC) of European Space Agency (ESA) and Center for Orbit Determination in Europe (CODE) IONEX products, especially in 2008 and 2009 when the solar activities were rather quiet. To improve this situation, we directly implement non-negative physical constraints of ionosphere for global ionosphere maps (GIM) with spherical harmonic functions. Mathematically, we propose an inequality-constrained least squares method by imposing non-negative inequality constraints in the areas where negative VTEC values may occur to reconstruct GIM models. We then apply the new method to process the IGS data in 2008. The results have shown that the new algorithm efficiently eliminates the unwanted behavior of negative VTEC values, which could otherwise often be seen in the current CODE and ESA GIM products in both middle and high latitude areas of the Southern Hemisphere (45°S∼90°S) and the Northern Hemisphere (50°N∼90°N). About 64% of GPS receivers’ DCBs have been significantly improved. Finally, we compare the GIM results between with and without the inequality constraints, which has clearly shown that the GIM result with inequality constraints is significantly better than that without the inequality constraints. The inequality-constrained GIM result is also highly consistent with the final IGS products in terms of root mean squared (RMS) and mean VTEC.     

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.      

On the estimation of regional covariance functions of TEC variations over Canada

Spatial and temporal variations of Total Electron Content (TEC) can affect GNSS high accuracy positioning. Enhanced estimation of ionospheric variations and their de-correlation can benefit differential and point positioning rapid solutions. Global and regional TEC maps can provide the overall state of ionopsheric variations in space and time domains within their accuracy limits. In this paper, these maps are exploited to retrieve ionospheric variations by means of variograms and their associated covariance functions of TEC residuals over Canadian region during geomagnetically quiet and disturbed conditions. A number of theoretical variogram functions are reviewed for modeling covariance of TEC residuals. The variogram modeling of residuals during a strong geomagnetic storm revealed variances of one order of magnitude larger compared to a rather quiet condition. Variogram models are also used in regional and local kriging interpolation experiments and their performances are evaluated. Global maps of TEC RMS by International GNSS Service and two of its analysis centres are also compared over the Canadian region during a two-year period. Realistic representation of regional variances using estimated variograms when compared to global ionospheric RMS maps are also presented.     

基于BDS/GPS和经验模型的区域电离层建模

基于北斗卫星导航系统（BDS）和全球定位系统（GPS）实测电离层穿刺点（IPP）数据,结合国际参考电离层（IRI）经验模型历史数据,提出一种对区域二维电离层总电子含量（TEC）进行高精度建模的方法.针对缺乏穿刺点的区域内短时间电离层建模时精度较低且各时段穿刺点空间分布不同的问题,该方法使用IRI模型在建模区域内均匀添加虚拟穿刺点数据,并根据与实测穿刺点的距离,使用构造的权重计算公式赋予其动态权重值,通过加权最小二乘法进行球谐模型参数解算.与欧洲定轨中心（CODE）发布的全球电离层图（GIM）进行数据比对发现,相对于只使用BDS/GPS实测穿刺点数据的建模方法,利用本文建模方法计算获得的垂直总电子含量（VTEC）值对缺乏实测穿刺点的区域精度有明显的提升.      

基于BP神经网络技术的电离层VTEC融合

随着电离层探测技术的不断发展,电离层观测资料也越来越多,只使用单一的观测资料会出现电离层反演精度不高的问题。为了提高电离层的反演精度,使用BP神经网络技术将地基反演和国际参考电离层(international reference ionosphere,IRI)模型的垂直总电子含量（vertical total electron content,VTEC）数据进行有效融合。在温带地区\[35°(N)~45°(N),60°(E)~80°(E)\]进行电离层反演试验,结果表明基于BP神经网络技术的电离层数据融合和地基反演获得的电离层VTEC精度都比较高,但是基于BP神经网络的电离层数据融合反演精度比地基反演更高,所以基于BP神经网络技术的数据融合能够提高电离层的反演精度。     

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.     

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.      

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.     

A method of estimating GPS instrumental biases with a convolution algorithm

This paper presents a method of deriving the instrumental differential code biases (DCBs) of GPS satellites and dual frequency receivers. Considering that the total electron content (TEC) varies smoothly over a small area, one ionospheric pierce point (IPP) and four more nearby IPPs were selected to build an equation with a convolution algorithm. In addition, unknown DCB parameters were arranged into a set of equations with GPS observations in a day unit by assuming that DCBs do not vary within a day. Then, the DCBs of satellites and receivers were determined by solving the equation set with the least-squares fitting technique. The performance of this method is examined by applying it to 361?days in 2014 using the observation data from 1311 GPS Earth Observation Network (GEONET) receivers. The result was crosswise-compared with the DCB estimated by the mesh method and the IONEX products from the Center for Orbit Determination in Europe (CODE). The DCB values derived by this method agree with those of the mesh method and the CODE products, with biases of 0.091?ns and 0.321?ns, respectively. The convolution method's accuracy and stability were quite good and showed improvements over the mesh method.     

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.     

A MARS-based method for estimating regional 2-D ionospheric VTEC and receiver differential code bias

The geometry-free linear combination of dual-frequency GNSS reference station ground observations are currently used to build the Vertical Total Electron Content (VTEC) model of the ionosphere. As it is known, besides ionospheric delays, there are differential code bias (DCB) of satellite (SDCB) and receiver (RDCB) in the geometry-free observation equation. The SDCB can be obtained using the International GNSS Service (IGS) analysis centers, but the RDCB for regional and local network receivers are not provided. Therefore, estimating the RDCB and VTEC model accurately and simultaneously is a critical factor investigated by researchers. This study uses Multivariate Adaptive Regression Splines (MARS) to estimate the VTEC approximate model and then substitutes this model in the observation equation to form the normal equation. The least squares method is used to solve the RDCB and VTEC model together. The research findings show that this method has good modeling effectiveness and the estimated RDCB has good reliability. The estimated VTEC model applied to GPS single-frequency precise point positioning has better positioning accuracy in comparison to the IGS global ionosphere map (GIM).