电离层周日变化对解算GPS硬件延迟稳定性的影响

针对电离层周日变化特征分析了其可能对SCORE方法估算的硬件延迟稳定性的影响. 利用BJFS以及XIAM台站的GPS观测数据, 解算了位于太阳活动高年(2001年)和太阳活动低年(2009年)的卫星硬件延迟并分析了估算的硬件延迟的稳定性. 研究发现, 电离层周日变化对估算的硬件延迟稳定性具有一定影响, 但是利用不同台站所得到的卫星硬件延迟稳定性在昼夜不同时间上的解算结果存在一定差异. 电离层周日变化对利用 BJFS台站数据解算的硬件延迟稳定性日夜差异较为明显, 在太阳活动高年利用XIAM 台站数据解算的硬件延迟日夜稳定性差异不很明显, 由于XIAM台站处于电离层赤道异常峰附近, 夜间电离层变化很大, 因此对比中纬度地区, 电离层周日变化对赤道异常峰附近地区硬件延迟稳定性解算结果的影响相对较小, 但在太阳活动低年, 其影响仍较为显著.      

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.      

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.      

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.      

基于GPS遥感的延迟映射接收机关键技术

全球卫星定位系统GPS(Global Positioning System)广泛应用于定位和导航,还可利用海面对GPS信号产生的散射效应进行微波遥感,是一种新型微波遥感手段.首先介绍了GPS海洋遥感测风技术产生背景及特点,给出了GPS散射信号测量技术理论基础,重点分析了延迟映射接收机设计中提高采样信号信噪比、双射频前端电路设计、计算反射点延迟、接收机工作模式、内嵌软件处理等5项关键技术.设计的延迟映射接收机样机在天津近海完成了首次搭载飞行试验,试验结果表明,延迟映射接收机可同时接收直射和海面散射卫星信号并输出导航定位解,正确计算镜面散射点码延迟,准确接收海面散射的GPS卫星信号,且散射信号信噪比达到了14.9 dB以上,接收机输出为反演海面风场提供了准确的基础数据,这种方式可推广到遥感探测陆地土壤湿度、海冰厚度、海浪高度等领域.      

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.      

流星雷达系统相位差偏差的估计和校正

介绍了一种新的流星雷达系统的相位偏差估计和校正方法.利用流星回波的观测数据,用回波信号在各个接收通道之间的相位差,结合干涉式接收天线阵的几何关系,建立了各天线相位差测量值与偏差值之间的线性方程组,利用最小二乘法求解方程组,得到了流星雷达系统各个接收通道之间的相位差偏差估计值及校正后的流星回波到达角.与已有的流星雷达相位偏差估计和校正的方法相比,这种方法可以通过流星雷达的观测数据来计破算雷达系统各个接收天线通道之间的相位差偏差量,而不需要增加额外的硬件,实现了对观测数据的事后处理,可以方便地对已有数据进行校正.以2004年4-6月的武汉流星雷达观测数据为例,计算了流星雷达系统的偏差估计量,并用校正后的数据来计算流星回波的空间位置.结果表明,校正后流星回波数在各个方向上随高度的分布比校正前更符合统计分布.      

地基单站GNSS的电离层VTEC高精度解算方法

利用IGS提供的双频GNSS观测数据，分析了Kalman方法解算电离层垂直总电子含量（Vertical Total Electron Content，VTEC）存在的问题，提出了Kriging-Kalman改进解算方法，并对两种方法解算的电离层VTEC进行分析和比较.结果表明:在低纬地区，当观测卫星数量发生改变时，Kalman方法解算的VTEC存在跳变异常，Kriging-Kalman方法解算的VTEC变化较为平稳，不存在跳变现象.对比分析耀斑期间两种方法解算VTEC的变化，发现Kalman方法解算的VTEC变化明显小于耀斑引起VTEC的增量；Kriging-Kalman方法解算结果与实际变化相一致.表明Kriging-Kalman方法计算精度更高，能够更精确计算耀斑等剧烈异常空间天气活动期间的VTEC及其变化，有利于电离层VTEC日常精确监测、研究和工程应用.      

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.      

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.      

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.     

一种地基GNSS接收机差分码偏差估算方法

GNSS不同频点间的码伪距作差会引入信号的差分码偏差(DCB),包括GNSS卫星及地面接收机的DCB.本文提出一种地基GNSS接收机差分码偏差参数估算方法,首先由电离层文件参数作线性插值,计算出电离层延迟误差.之后对IGS站观测文件进行加权最小二乘法估计,得到GPS卫星和地面GNSS接收机的L1C频点和L2P频点间码偏...     

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.     

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.     

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.     

基于硬件信号模拟器的电离层TEC监测仪 差分码偏差长期变化

利用硬件信号模拟器可以标定电离层TEC监测仪的差分码偏差.通过对相同接收机时隔近41.5月进行的两次差分码偏差标定实验,以GPS系统为例分析了硬件标定法得到的差分码偏差随时间的长期变化情况.结果表明:接收机差分码偏差均值从第一次实验的16.122ns增加至第二次实验的16.749ns,在约41.5月的时间内增加约0.627ns,月增量为0.0151ns,增加比较缓慢;第二次实验的差分码偏差标准差也有所增加,但增量也不大（均值分别为0.05ns和0.07ns）.此外,两次标定实验的TEC测量精度（均方根误差）均达到约0.3TECU,对应的差分码偏差误差约0.1ns,这说明该接收机差分码偏差变化的一致性较好.若不加以再次标定,第二次实验时TEC测量误差将增加至约1.8TECU,月增量约为0.0434TECU.      

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.     

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).     

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%。