不同太阳活动条件下电离层形态对估算GPS系统硬件延迟的影响

利用两个中纬度台站GPS观测数据提取的GPS卫星硬件延迟,分析了不同太阳活动情况下估算的硬件延迟稳定性和统计特征,结合同期电离层观测数据,研究了电离层状态对硬件延迟估算结果的影响.研究结果表明,基于太阳活动高年(2001年)GPS观测数据估算的硬件延迟稳定性要低于太阳活动低年GPS观测数据的估算结果,利用2001年GPS数据估算的卫星硬件延迟年标准偏差(RMS)平均值约为1TECU,而2009年GPS数据估算的卫星硬件延迟年标准偏差平均值约为0.8TECU.通过对2001年和2009年北京地区电离层F₂层最大电子密度(N_mF₂)变化性分析,结合GPS硬件延迟估算方法对电离层时空变化条件的要求,认为硬件延迟稳定性与太阳活动强度的联系是由不同太阳活动条件下电离层变化的强度差异引起的.      

利用北斗观测数据实时监测中国区域电离层变化

北斗卫星导航信号采用三个频点工作,可以利用伪距双频组差方法解算电离层电子含量,为实时监视中国区域电离层变化提供新的技术手段.中国中低纬度处于电离层赤道异常变化区,在北纬20°±5°区域时常发生较大梯度的电离层变化.利用北斗实时多频伪距和相位观测数据,采用相位平滑伪距方法计算电离层穿刺点电子含量,分析通过北斗系统GEO卫星监测的电离层周日变化特性;采用多面函数方法拟合中国区域1°×1°分辨率的电离层延迟量,每5min绘制一幅中国区域电离层图,观测区域所有电离层穿刺点拟合残差RMS为2.778TECU;分析北斗系统实时监测中国区域电离层异常情况,当发生电离层异常变化时,相邻两天的VTEC（Vertical Total Electronic Content）峰值相差约60TECU.      

夏季强对流活动对东亚低纬电离层不规则体影响的事件分析

利用海南台站和东南亚地区的多种地基和天基观测手段,对2014年7月28日夜间观测到的东亚低纬F区不规则体事件的时空变化及其物理过程进行分析。结果表明,海南台站观测到了罕见的长时间持续的F区电离层不规则体,不同手段观测到的电离层不规则体存在明显的形态差异。不同台站观测到的电离层不规则体活动存在明显的差异。海南台站经度区南北异常峰附近的TEC起伏活动在日落后至午夜附近明显增强,在午夜后明显减弱。C/NOFS卫星轨迹午夜后逐渐接近于磁赤道,且处于较低高度上,几乎总会观测到弱等离子体扰动/泡的发生,与该区域地基观测的弱电离层不规则体活动存在明显的联系。SWARM卫星在黎明海南台站附近经度区仍观测到较强的赤道异常双峰结构,且西侧异常峰区附近仍存在明显的等离子体密度耗空/泡结构。海南台站西侧磁赤道区附近（中南半岛）强对流活动（MCC）激发的重力波种子扰动对东亚低纬区等离子体泡及准周期结构的产生发挥了重要作用。      

磁静日电离层电势分布的形态学研究

利用理论模式GCITEM，在国际地磁参考场（IGRF）下，模拟了地磁平静条件下的电离层发电机主导的中低纬电离层电势分布，研究了太阳活动、季节、世界时和低层大气潮汐对电离层电势的调节作用。结果表明，各种条件下中低纬电势全局分布基本一致，都具有两个正电势峰值（源）和一个负电荷峰值（汇）；电势分布存在明显的季节和世界时差异；中低纬电离层电势峰值差随着太阳活动的增强明显增加，并在一定太阳活动高值后趋于饱和；周日迁移潮主要影响赤道地区，导致电势峰值差增加，而半周日迁移潮主要影响中纬度地区，导致电势峰值差减小。     

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.      

地磁暴期间中国中低纬电离层的CIT研究

利用电离层层析成像技术(Computerized Ionospheric Tomography, CIT)处理115°E子午圈附近6个台站的GPS观测数据, 分析了2004年11月地磁暴期间中国中低纬电离层的响应情况. 结果表明, 电离层呈正相扰动, 且不同高度上的响应不同, 800 km以下电子密度有不同程度的增加, 且在峰值高度附近增幅最大, 800 km以上地磁暴的影响并不显著; 伴随地磁能量的注入, 赤道异常峰极向扩展; 随磁扰强度的降低, 电子密度也逐渐恢复至平静水平. 这些结果与以往的理论和观测结果一致, 初步估计扰动是由热层暴环流引起的, 并受到赤道异常峰移动的影响.      

利用IGS-TEC数据分析中国华南地区电离层赤道异常北驼峰的变化特征

利用2010年11月至2011年10月IGS提供的全球电子浓度总含量(TEC)数据, 分析太阳活动上升期华南地区(经度110°E, 纬度5°—35°N) 上空电离层赤道异常(EIA)北驼峰的变化特征. 结果显示, 电离层赤道异常北驼峰区TEC峰值I具有明显的季节和半年变化特征; 北驼峰峰值出现的时间T和纬度L的日变化有一个相对较大的变化区间, 其季节和半年变化特征并不明显; 太阳活动对北驼峰变化影响比较明显, 而地磁活动对北驼峰变化影响不明显.      

赤道异常区GPS-TEC与系统硬件偏差的反演

提出了一种基于最小二乘的赤道异常区GPS-TEC与系统硬件偏差的反演方法.利用设置在福州、厦门、广州和南宁4个台站的观测数据,可以得到GPS卫星和接收机的硬件偏差以及(20°～28°N,105°～123°E)区域中48个3°×1°网格的TEC(时间分辨率为15 min).应用于2006年观测数据,得到了较稳定的系统硬件偏差,其中卫星硬件偏差值与欧洲定轨中心公布的结果接近,得到的TEC具有合理的日变化和季节变化特征.该反演方法可以应用于赤道异常区电离层的研究.      

北驼峰区电离层GPS卫星闪烁事件时空特征及对通信的影响

基于子午工程北大深圳站（22.59°N,113.97°E）电离层GPS双频接收机在2011年1月1日至2017年12月31日连续7年的长时间序列闪烁和TEC观测数据,分析不同太阳活条件下华南赤道异常北驼峰区观测到的GPS卫星L波段电离层闪烁事件时空分布特征及其对通信的影响.结果表明:GPS闪烁事件几乎都发生在夜间,且主要发生在春秋分月份;在不同太阳活动条件下,夜间GPS闪烁事件都主要发生在北驼峰区域靠近磁赤道的一侧,且GPS闪烁事件存在明显的东-西侧天区不对称性,即在台站西侧天区发生的闪烁事件明显偏多;在不同太阳活动条件下,弱闪烁事件伴随的TEC耗尽和卫星失锁事件比例相对较低,强闪烁事件则大部分都伴随着TEC耗尽和卫星失锁事件的发生.      

MGEX北斗差分码偏差两种精确处理方法对比分析

差分码偏差是北斗卫星导航系统（BDS）在高精度定位和电离层建模中需精确处理的系统误差之一.利用MGEX发布的2017年全年和2018年6月的BDS卫星的差分码偏差数据,比较分析了DLR和CAS分别解算的BDS卫星差分码偏差的日解值、月平均值和稳定性的变化特性.分析结果表明,DLR与CAS估算的BDS卫星差分码偏差值差异不大,具有较好的一致性;2017年CAS估算的BDS卫星C2I-C6I差分码偏差稳定性略优于DLR,C2I-C7I差分码偏差稳定性与DLR相当,且均具有较高稳定性;2018年6月DLR C2I-C6I差分码偏差月平均值稳定性优于CAS;C2I-C7I差分码偏差的稳定性明显优于C2I-C6I差分码偏差,卫星差分码偏差月平均值稳定性优于日解值稳定性.      

Estimation and analysis of GPS receiver differential code biases using KGN in Korean Peninsula

The total electron content (TEC) estimation by the Global Positioning System (GPS) can be seriously affected by the differential code biases (DCB), referred to as inter-frequency biases (IFB), of the satellite and receiver so that an accuracy of GPS–TEC value is dependent on the error of DCBs estimation. In this paper, we proposed the singular value decomposition (SVD) method to estimate the DCB of GPS satellites and receivers using the Korean GPS network (KGN) in South Korea. The receiver DCBs of about 49 GPS reference stations in KGN were determined for the accurate estimation of the regional ionospheric TEC. They obtained from the daily solution have large biases ranging from +5 to +27 ns for geomagnetic quiet days. The receiver DCB of SUWN reference station was compared with the estimates of IGS and JPL global ionosphere map (GIM). The results have shown comparatively good agreement at the level within 0.2 ns. After correction of receiver DCBs and knowing the satellite DCBs, the comparison between the behavior of the estimated TEC and that of GIMs was performed for consecutive three days. We showed that there is a good agreement between KASI model and GIMs.     

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.     

Estimation of differential code biases with Jason-2/3 onboard GPS observations

With the continuous deployment of Low Earth Orbit (LEO) satellites, the estimation of differential code biases (DCBs) based on GNSS observations from LEO has gained increasing attention. Previous studies on LEO-based DCB estimation are usually using the spherical symmetry ionosphere assumption (SSIA), in which a uniform electron density is assumed in a thick shell. In this study, we propose an approach (named the SHLEO method) to simultaneously estimate the satellite and LEO onboard receiver DCBs by modeling the distribution of the global plasmaspheric total electron content (PTEC) above the satellite orbit with a spherical harmonic (SH) function. Compared to the commonly used SSIA method, the SHLEO model improves the GPS satellite DCB estimation accuracy by 13.46% and the stability by 22.34%, respectively. Compared to the GPS satellite DCBs estimated based on the Jason-3-only observations, the accuracy and monthly stability of the satellite DCBs can be improved by 14.42% and 26.8% when both Jason-2 and Jason-3 onboard observations are jointly processed. Compared with the Jason-2 solutions, the GPS satellite DCB estimates based on the fusion of Jason-2 and Jason-3 observations have an improved consistency of better than 18.26% and 9.71% with the products provided by the Center for Orbit Determination in Europe (CODE) and Chinese Academy of Sciences (CAS). Taking the DCB products provided by the German Aerospace Center (DLR) as references, there is no improvement in accuracy of the GPS satellite DCB estimates based on the fusion of Jason-2 and Jason-3 observations than the Jason-2 solutions alone. A periodic variation is found in the time series of both the Jason-3 and Jason-2 onboard receiver DCB estimates. Preliminary analysis of the PTEC distribution based on the estimated SH coefficients are also presented.     

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.     

Differential code bias estimation based on uncombined PPP with LEO onboard GPS observations

Differential Code Bias (DCB) is an essential correction that must be provided to the Global Navigation Satellite System (GNSS) users for precise position determination. With the continuous deployment of Low Earth Orbit (LEO) satellites, DCB estimation using observations from GNSS receivers onboard the LEO satellites is drawing increasing interests in order to meet the growing demands on high-quality DCB products from LEO-based applications, such as LEO-based GNSS signal augmentation and space weather research. Previous studies on LEO-based DCB estimation are usually using the geometry-free combination of GNSS observations, and it may suffer from significant leveling errors due to non-zero mean of multipath errors and short-term variations of receiver code and phase biases. In this study, we utilize the uncombined Precise Point Positioning (PPP) model for LEO DCB estimation. The models for uncombined PPP-based LEO DCB estimation are presented and GPS observations acquired from receivers onboard three identical Swarm satellites from February 1 to 28, 2019 are used for the validation. The results show that the average Root Mean Square errors (RMS) of the GPS satellite DCBs estimated with onboard data from each of the three Swarm satellites using the uncombined PPP model are less than 0.18 ns when compared to the GPS satellite DCBs obtained from IGS final daily Global Ionospheric Map (GIM) products. Meanwhile, the corresponding average RMS of GPS satellite DCBs estimated with the conventional geometry-free model are 0.290, 0.210, 0.281 ns, respectively, which are significantly larger than those obtained with the uncombined PPP model. It is also noted that the estimated GPS satellite DCBs by Swarm A and C satellites are highly correlated, likely attributed to their similar orbit type and space environment. On the other hand, the Swarm receiver DCBs estimated with uncombined PPP model, with Standard Deviation (STD) of 0.065, 0.037 and 0.071 ns, are more stable than those obtained from the official Swarm Level 2 products with corresponding STD values of 0.115, 0.101, and 0.109 ns, respectively. The above indicates that high-quality DCB products can be estimated based on uncombined PPP with LEO onboard observations.     

Estimation of QZSS differential code biases using QZSS/GPS combined observations from MGEX

As an important error source in Global Navigation Satellite System (GNSS) positioning and ionospheric modeling, the differential code biases (DCB) need to be estimated accurately, e.g., the regional Quasi-Zenith satellite system (QZSS). In this paper, the DCB of QZSS is estimated by adopting the global ionospheric modeling method based on QZSS/GPS combined observations from Multi-GNSS experiment (MGEX). The performance of QZSS satellite and receiver DCB is analyzed with observations from day of year (DOY) 275–364, 2018. Good agreement between our estimated QZSS satellite DCB and the products from DLR and CAS is obtained. The bias and root mean square (RMS) of DCB are mostly within ±0.3 ns. The day-to-day fluctuation of the DCB time series is less than 0.5 ns with about 96% of the cases for all satellites. However, the receiver DCB is a little less stable than satellite DCB, and their standard deviations (STDs) are within 1.9 ns. The result shows that the stability of the receiver DCBs is not significantly related to the types of receiver or antenna.     

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.      

基于三频数据的北斗卫星导航系统DCB参数精度评估方法

差分码偏差（Differential Code Biases,DCB）参数作为导航电文中重要的一项,是影响用户PNT服务的主要误差源之一。北斗卫星导航系统（后文简称“北斗系统”）发射三个频点的导航信号,在导航电文中需要发播卫星的2个TGD（Timing Group Delay）参数。文章首先介绍了北斗系统卫星DCB参数最小二乘解算与形式误差评估;其次根据北斗系统三频特点,提出了不同频点组合计算垂直方向电离层电子总含量（VTEC）互差的DCB精度定量评估方法,并与IGS(International GNSS Service)提供的GPS卫星DCB精度进行比较;最后,详细分析了DCB参数精度对用户等效距离误差（UERE）计算和定位计算的影响,分别采用卫星出场标定DCB参数和经过解算DCB参数进行评估。实测数据分析结果表明,北斗系统卫星DCB参数解算形式误差与IGS解算GPS卫星DCB参数形式误差相当,但受卫星类型和解算测站的几何分布限制,北斗系统卫星DCB参数解算不确定度相比IGS略差,估计精度优于0.5ns,不同频率组合计算VTEC互差绝对值均值优于0.6TECU。相比采用卫星出场标定值,采用系统解算DCB参数后,双频用户三维位置误差改善13.80%～47.42%。     

GPS卫星信标信噪比的统计分析

GPS卫星信标信噪比(SNR)受到卫星上的发射机增益、地面站的接收机增益、卫星与接收机之间的几何距离、接收机处的仰角、信标传播路径上电离层介质衰减等因素的共同影响.首先提出了一种从SNR观测数据中分离出SNR在电离层中衰减的算法,并应用于MANA接收站(273.751°E,12.149°N)2003年的观测数据,得到了一个电离层介质引起的对L波段信标SNR衰减日变化的平均情况.通过与IRI模式计算的电波垂直穿过电离层时衰减的SNR比较发现,由我们得到的SNR在电波垂直穿过电离层时的衰减与IRI模式计算的衰减随地方时的变化符合得比较好.