Klobuchar模型的实用分析与改进

电离层延迟误差是无线电信号传播中不可忽视的误差源.GPS特许用户利用双频接收机的双频观测值直接对电离层延迟进行实时测定,其所得结果精度很高.多数普通用户所使用的单频接收机依靠电离层模型对其进行误差修正,效果不很理想.本文通过WUHN观测站双频接收机10天的实测数据对GPS广播星历采用的Klobuchar模型进行了验证,其结果与前人论述相一致.此外,经由反映太阳活动强度的太阳相对黑子数对Klobuchar模型提出了新的改进方法.实验数据结果表明,该方法对此模型修正效果有大幅提升,对原模型修正效果>50%的修正率由60%左右提升至85%以上,>80%的修正率由10%左右提升至40%以上.在实际应用中单频接收机用户可以参考本文改进方法对Klobuchar模型进行修正.      

利用GPS技术实时监测上海区域电离层变化

基于GPS技术实时监测电离层变化原理, 利用载波平滑伪距观测值建立区域电离层模型的方法, 计算了电离层延迟量和硬件延迟, 根据硬件延迟值相对稳定的特点, 采取一定时段求解出硬件延迟量, 对实时硬件延迟量进行预报, 进而实时分离GPS信号传播路径上的垂直总电子含量VTEC. 利用上海区域内的GPS网的观测数据, 建立实时上海区域电离层延迟模型, 监测上海区域的电离层变化. 数据分析结果表明, 这种方法的内符合精度优于3 TECU.      

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.      

北斗区域Klobuchar改进模型及其修正精度分析

北斗卫星导航系统采用Klobuchar模型修正单频接收机用户的电离层延迟误差,由于此模型从亚洲地区应用角度考虑,在某一特定区域的修正精度甚至不足50%。为进一步提高区域电离层延迟修正精度,提出在原模型8个改正参数的基础上增加5个关键参数的Klobuchar改进模型,并采用松弛迭代与直线搜索法中的黄金分割相结合的算法对新增参数进行求解。以天津及其附近区域为例,利用GPStation6接收机采集到的实测数据对改进模型与原模型进行计算。将国际全球导航卫星系统服务组织（International GNSS Service,IGS）发布的全球电离层格网数据作为参考值,对比分析改进模型与原模型的修正精度。结果表明,区域Klobuchar改进模型在天津及其附近区域的电离层延迟平均修正精度比原模型提升了10.46%,平均修正精度达到77.51%。     

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（international GNSS monitoring & assessment system，iGMAS）发布的高精度电离层格网数据作为对照，对Klobuchar电离层模型误差进行计算和分析，结果发现在中纬度区域误差存在明显的周期性特征。为进一步提高Klobuchar电离层模型在中纬度区域的改正精度，建立了基于粒子群优化反向传播（back propagation，BP）神经网络的Klobuchar电离层误差预测模型,并以2019年10月的采样数据为例进行误差预测。结果表明，用该模型对中纬度区域电离层延迟提供误差补偿，可将精度提高到90%左右。     

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，进而影响最后求解的电离层延迟的准确性.本文选取了美国19个参考站的GPS双频观测数据，利用卡尔曼滤波实时估算电离层模型系数以及频间偏差.在滤波过程中，通过将先验频间偏差的估计方差引入测量噪声方差，实现对测量噪声协方差矩阵的优化.计算结果表明，优化后得到的卫星频间偏差与欧洲定轨中心（Center for Orbit Determination in Europe，CODE）得到的频间偏差更接近.将优化后的电离层延迟代入伪距解算，得到的位置误差的标准差在东向和天顶向分别下降了12.5%和15.4%，天顶向误差平均值下降了17.6%，定位精度得到提高.      

北斗三号电离层模型性能分析

根据北斗卫星导航系统三步走战略，北斗三号系统空中星座在2020年左右完成部署，信号的覆盖范围从亚太大部分地区扩展至全球.实际上自2018年底北斗三号系统已经可以初步提供全球服务.相应地，北斗系统的单频电离层模型从只适用于亚太大部分地区的BDSKlob模型发展到适用于全球范围的BDGIM模型.为分析北斗三号电离层模型的性能，以IGS GIM最终数据为参考，比较了2019年3月1-31日期间北斗BDGIM模型、BDSKlob模型以及GPSKlob模型在不同时段不同地区的改正效果.结果表明:北斗三号BDGIM模型在中国区域的改正率达75%以上，优于BDSKlob模型59%的改正率；在全球范围的改正率达60%，优于GPSKlob模型49%的改正率.除南半球高纬度地区外，BDGIM模型的电离层误差值均小于GPSKlob模型，其在垂直方向的电离层均方根误差值优于6TECU.      

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。     

单接收机GNSS数据组合硬件延迟的联合求解方法

利用GNSS观测数据解算TEC的最大误差源是硬件延迟,包括卫星硬件延迟和接收机硬件延迟.在单接收机情况下,由于数据稀疏以及接收到的卫星信号时间不对齐等特点,已有的解算硬件延迟方法的求解结果往往不理想.在应用局域模式拟合方法和SCORE方法求解单接收机数据基础上,利用局域模型拟合法在电离层平静期拟合较准确的优点,提出一种联合改进方法,同时改正了SCORE方法解算过程中约束过强的缺点.通过利用GPStation-6接收机的GPS和BDS实际观测数据进行解算分析,验证了所提方法的有效性与准确性.      

北斗三号系统广域差分服务精度评估

为了保证北斗系统广域差分服务的平稳过渡，北斗三号系统（BDS-3）通过GEO卫星B1I/B3I信号播发北斗二号协议广域差分改正信息，包括等效钟差改正数与格网点电离层信息。分析了增加BDS-3卫星后，等效钟差改正数和格网点电离层信息的特征，并对BDS-2和BDS-3的用户差分距离误差（UDRE）进行了对比。联合BDS-2和BDS-3实测数据，对BDS-3广域差分服务定位精度进行了评估。分析结果表明:BDS-2卫星广播星历空间信号用户等效距离误差（UERE）约为1 m，经过等效钟差改正数后，用户差分距离误差约为0.3 m；BDS-3卫星广播星历空间信号用户等效距离误差约为0.4 m，经过等效钟差改正数后，用户差分距离误差约为0.2 m。等效钟差改正数可以修正广播电文更新带来的空间信号阶跃误差，显著提升卫星空间信号精度。与基本导航系统播发的Klobuchar 8模型，广域差分系统所播发的格网点电离层信息可将电离层误差修正精度提高约18%。与单独BDS-2卫星相比，BDS-2/BDS-3卫星联合条件下，基本导航的单频用户和双频用户定位精度可分别提升26%和41%；广域差分服务的单频用户定位精度为2.4 m，双频用户定位精度为1.7 m，单频用户和双频用户定位精度分别提升13%和41%。      

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.     

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.      

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).     

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.     

Analysis of GNSS clock prediction performance with different interrupt intervals and application to real-time kinematic precise point positioning

Continuous and timely real-time satellite orbit and clock products are mandatory for real-time precise point positioning (RT-PPP). Real-time high-precision satellite orbit and clock products should be predicted within a short time in case of communication delay or connection breakdown in practical applications. For prediction, historical data describing the characteristics of the real-time orbit and clock can be used as the basis for performing the prediction. When historical data are scarce, it is difficult for many existing models to perform precise predictions. In this paper, a linear regression model is used to predict clock products. Seven-day GeoForschungsZentrum (GFZ) final clock products sampled at 30 s are used to analyze the characteristics of GNSS clocks. It is shown that the linear regression model can be used as the prediction model for the satellite clock products. In addition, the accuracy of the clock prediction for different satellites are analyzed using historical data with different periods (such as 2 and 10 epochs). Experimental results show that the accuracy of the clock with the linear regression prediction model using historical data with 10 epochs is 1.0 ns within 900 s. This is higher accuracy than that achieved using historical data of 2 epochs. Finally, the performance analysis for real-time kinematic precise point positioning (PPP) is provided using GFZ final clock prediction results and state space representation (SSR) clock prediction results when communication delay or connection breakdown occur. Experimental results show that the positioning accuracy without prediction is better than that with prediction in general, whether using the final clock product or the SSR clock product. For the final clock product, the positioning accuracy in the north (N), east (E), and up (U) directions is better than 10.0 cm with all visible GNSS satellites with prediction. In comparison, the 3D positioning accuracy of N, E, and U directions with visible GNSS satellites whose prediction accuracy is better than 0.1 ns using historical data of 10 epochs is improved from 15.0 cm to 7.0 cm. For the SSR clock product, the positioning accuracy of N, E, and U directions is better than 12.0 cm with visible GNSS satellites with prediction. In comparison, the 3D positioning accuracy of N, E, and U directions with visible GNSS satellites whose prediction accuracy is better than 0.1 ns using historical data of 10 epochs is improved from 12.0 cm to 9.0 cm.     

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.     

SHAKING: Adjusted spherical harmonics adding KrigING method for near real-time ionospheric modeling with multi-GNSS observations

Precise positioning based on Global Navigation Satellite System (GNSS) technique requires high accuracy ionospheric total electron content (TEC) correction models to account for the ionospheric path delay errors. We present an adjusted Spherical Harmonics Adding KrigING method (SHAKING) approach for regional ionospheric vertical TEC (VTEC) modeling in real time. In the proposed SHAKING method, the VTEC information over the sparse observation data area is extrapolated by the Adjusted Spherical Harmonic (ASH) function, and the boundary distortion in regional VTEC modeling is corrected by the stochastic VTEC estimated using Kriging interpolation. Using real-time GPS, GLONASS and BDS-2/3 data streams of the Crust Movement Observation Network of China (CMONOC), the SHAKING-based regional ionospheric VTEC maps are re-constructed over China and its boundary regions. Compared to GNSS VTECs derived from the independent stations, the quality of SHAKING solution improves by 13–31% and 6–33% with respect to the ASH-only solution during high and low geomagnetic periods, respectively. Compared to the inverse distance weighting (IDW) generated result, significant quality improved of SHAKING-based VTEC maps is also observed, especially over the edge areas with an improvement of 60–80%. Overall, the proposed SHAKING method exhibits notable advantage over the existing regional VTEC modeling techniques, which can be used for regional TEC modeling and associated high-precision positioning applications.     

Multi-GNSS contributions to differential code biases determination and regional ionospheric modeling in China

Due to the limited number and uneven distribution globally of Beidou Satellite System (BDS) stations, the contributions of BDS to global ionosphere modeling is still not significant. In order to give a more realistic evaluation of the ability for BDS in ionosphere monitoring and multi-GNSS contributions to the performance of Differential Code Biases (DCBs) determination and ionosphere modeling, we select 22 stations from Crustal Movement Observation Network of China (CMONOC) to assess the result of regional ionospheric model and DCBs estimates over China where the visible satellites and monitoring stations for BDS are comparable to those of GPS/GLONASS. Note that all the 22 stations can track the dual- and triple-frequency GPS, GLONASS, and BDS observations. In this study, seven solutions, i.e., GPS-only (G), GLONASS-only (R), BDS-only (C), GPS + BDS (GC), GPS + GLONASS (GR), GLONASS + BDS (RC), GPS + GLONASS + BDS (GRC), are used to test the regional ionosphere modeling over the experimental area. Moreover, the performances of them using single-frequency precise point positioning (SF-PPP) method are presented. The experimental results indicate that BDS has the same ionospheric monitoring capability as GPS and GLONASS. Meanwhile, multi-GNSS observations can significantly improve the accuracy of the regional ionospheric models compared with that of GPS-only or GLONASS-only or BDS-only, especially over the edge of the tested region which the accuracy of the model is improved by reducing the RMS of the maximum differences from 5–15 to 2–3 TECu. For satellite DCBs estimates of different systems, the accuracy of them can be improved significantly after combining different system observations, which is improved by reducing the STD of GPS satellite DCB from 0.243 to 0.213, 0.172, and 0.165 ns after adding R, C, and RC observations respectively, with an increment of about 12.3%, 29.4%, and 32.2%. The STD of GLONASS satellite DCB improved from 0.353 to 0.304, 0.271, and 0.243 ns after adding G, C, and GC observations, respectively. The STD of BDS satellite DCB reduced from 0.265 to 0.237, 0.237 and 0.229 ns with the addition of G, R and GR systems respectively, and increased by 10.6%, 10.4%, and 13.6%. From the experimental positioning result, it can be seen that the regional ionospheric models with multi-GNSS observations are better than that with a single satellite system model.