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1.
GNSS observables for ionospheric estimation are commonly based on carrier-to-code leveling (CCL) and precise point positioning (PPP) methods. The CCL method is a geometry-free method which uses carrier phase to level pseudorange observation for decreasing multipath error and observation noise. However, the ionospheric observable based on the CCL has been proven to be affected by leveling errors. The leveling errors are caused by pseudorange multipath and intraday variation of receiver DCB. To obtain more accurate ionospheric observable, the PPP method takes advantage of precise satellite-to-ground range for retrieving slant total electron content and is less affected by the leveling errors. Previous studies have only proven that the ionospheric observables extracted by the two methods are affected by the leveling errors. The influence on ionospheric observable by the pseudorange inter-receiver satellite bias (IRSB) of the receiver has not been taken into consideration. Also, the magnitude of the differences between the ionospheric observables extracted by the two methods has also not been given. In this work, three methods, namely, the CCL, the conventional ionospheric-free PPP method which uses the ionospheric-free Hatch–Melbourne–Wubbena (HMW) function, and the University of Calgary (UOFC) PPP method, are selected to analyze and compare the differences of ionospheric observables and the global ionospheric maps, using a large number of measured data from international GNSS service global stations. Experimental results show that the accuracy of ionospheric observables obtained by the three methods is not only related to the leveling error, but also pseudorange IRSB. The IRSB of the receiver exerts a major effect on the ionospheric observables obtained by the CCL method and a minor effect on the ionospheric observables obtained by the HMW and UOFC methods. The accuracies in the latter case are similar and superior to those obtained by the CCL. The differences of the ionospheric observables obtained by the CCL and UOFC methods, or the CCL and HMW methods, are at decimeter level, whereas the difference of the ionospheric observables obtained by the UOFC and HMW methods is at centimeter level. The UOFC method presented the highest single-frequency pseudorange positioning accuracy using estimated global ionospheric products, followed by the HMW and the CCL methods which presented the lowest positioning accuracy.  相似文献   

2.
在全球定位系统(Global Positioning System,GPS)中,接收机硬件延迟引起的码偏差和相位偏差是影响精密授时、电离层建模以及非差模糊度解算的重要因素。利用GPS对电离层总电子含量进行估计和建模时,通常假定GPS接收机硬件延迟偏差是稳定不变的量,对其可能存在的波动及影响因素考虑不充分。因此,对GPS接收机硬件延迟偏差的时变特性进行分析,有助于提高电离层电子含量估值的准确性和可靠性。分析了GPS接收机差分码偏差(differential code bias,DCB)和差分相位偏差(differential phase bias,DPB)单历元及单天解的时间变化特性,并对温度变化与接收机DCB、DPB变化之间的相关性进行了实验探究。结果表明,接收机重启前后其DCB值会发生突变,重启之后接收机DCB和DPB大约需要25 min才能趋于稳定。接收机DCB和DPB并不能长期保持稳定,实验数据显示,在2~3 h内,DCB的变化量可以达到0.8 m左右,DPB的变化量可以达到4 mm左右,接收机DCB和DPB的波动与周围环境温度的变化具有较强相关性。  相似文献   

3.
The Global Navigation Satellite System presents a plausible and cost-effective way of computing the total electron content (TEC). But TEC estimated value could be seriously affected by the differential code biases (DCB) of frequency-dependent satellites and receivers. Unlike GPS and other satellite systems, GLONASS adopts a frequency-division multiplexing access mode to distinguish different satellites. This strategy leads to different wavelengths and inter-frequency biases (IFBs) for both pseudo-range and carrier phase observations, whose impacts are rarely considered in ionospheric modeling. We obtained observations from four groups of co-stations to analyze the characteristics of the GLONASS receiver P1P2 pseudo-range IFB with a double-difference method. The results showed that the GLONASS P1P2 pseudo-range IFB remained stable for a period of time and could catch up to several meters, which cannot be absorbed by the receiver DCB during ionospheric modeling. Given the characteristics of the GLONASS P1P2 pseudo-range IFB, we proposed a two-step ionosphere modeling method with the priori IFB information. The experimental analysis showed that the new algorithm can effectively eliminate the adverse effects on ionospheric model and hardware delay parameters estimation in different space environments. During high solar activity period, compared to the traditional GPS + GLONASS modeling algorithm, the absolute average deviation of TEC decreased from 2.17 to 2.07 TECu (TEC unit); simultaneously, the average RMS of GPS satellite DCB decreased from 0.225 to 0.219 ns, and the average deviation of GLONASS satellite DCB decreased from 0.253 to 0.113 ns with a great improvement in over 55%.  相似文献   

4.
5.
The calibration errors on experimental slant total electron content (TEC) determined with global positioning system (GPS) observations is revisited. Instead of the analysis of the calibration errors on the carrier phase leveled to code ionospheric observable, we focus on the accuracy analysis of the undifferenced ambiguity-fixed carrier phase ionospheric observable determined from a global distribution of permanent receivers. The results achieved are: (1) using data from an entire month within the last solar cycle maximum, the undifferenced ambiguity-fixed carrier phase ionospheric observable is found to be over one order of magnitude more accurate than the carrier phase leveled to code ionospheric observable and the raw code ionospheric observable. The observation error of the undifferenced ambiguity-fixed carrier phase ionospheric observable ranges from 0.05 to 0.11 total electron content unit (TECU) while that of the carrier phase leveled to code and the raw code ionospheric observable is from 0.65 to 1.65 and 3.14 to 7.48 TECU, respectively. (2) The time-varying receiver differential code bias (DCB), which presents clear day boundary discontinuity and intra-day variability pattern, contributes the most part of the observation error. This contribution is assessed by the short-term stability of the between-receiver DCB, which ranges from 0.06 to 0.17 TECU in a single day. (3) The remaining part of the observation errors presents a sidereal time cycle pattern, indicating the effects of the multipath. Further, the magnitude of the remaining part implies that the code multipath effects are much reduced. (4) The intra-day variation of the between-receiver DCB of the collocated stations suggests that estimating DCBs as a daily constant can have a mis-modeling error of at least several tenths of 1 TECU.  相似文献   

6.
在传统多系统非差非组合精密单点定位(precise point positioning,PPP)模型中,电离层延迟会吸收部分接收机码硬件延迟,其估计值可能为负数。提出了一种估计接收机差分码偏差(differential code bias,DCB)参数的GPS(Global Positioning System)/BDS(BeiDou Navigation Satellite System)非组合PPP模型,将每个系统第1个频率上的接收机码硬件延迟约束为零,对接收机DCB进行参数估计,达到了分离电离层延迟和接收机码硬件延迟的目的,降低了接收机钟差和电离层延迟的相关程度。利用4个多星座实验(multi-GNSS experiment,MGEX)跟踪站的GPS/BDS数据进行了静态和动态PPP试验,结果表明,与不估计DCB参数的PPP模型相比,采用估计DCB参数PPP模型后,静态模式下定位精度和收敛速度平均提高了29.3%和29.8%,动态模式下定位精度和收敛速度平均提高了15.7%和21.6%。  相似文献   

7.
Vertical total electron content (VTEC) parameters estimated using global navigation satellite system (GNSS) data are of great interest for ionosphere sensing. Satellite differential code biases (SDCBs) account for one source of error which, if left uncorrected, can deteriorate performance of positioning, timing and other applications. The customary approach to estimate VTEC along with SDCBs from dual-frequency GNSS data, hereinafter referred to as DF approach, consists of two sequential steps. The first step seeks to retrieve ionospheric observables through the carrier-to-code leveling technique. This observable, related to the slant total electron content (STEC) along the satellite–receiver line-of-sight, is biased also by the SDCBs and the receiver differential code biases (RDCBs). By means of thin-layer ionospheric model, in the second step one is able to isolate the VTEC, the SDCBs and the RDCBs from the ionospheric observables. In this work, we present a single-frequency (SF) approach, enabling the joint estimation of VTEC and SDCBs using low-cost receivers; this approach is also based on two steps and it differs from the DF approach only in the first step, where we turn to the precise point positioning technique to retrieve from the single-frequency GNSS data the ionospheric observables, interpreted as the combination of the STEC, the SDCBs and the biased receiver clocks at the pivot epoch. Our numerical analyses clarify how SF approach performs when being applied to GPS L1 data collected by a single receiver under both calm and disturbed ionospheric conditions. The daily time series of zenith VTEC estimates has an accuracy ranging from a few tenths of a TEC unit (TECU) to approximately 2 TECU. For 73–96% of GPS satellites in view, the daily estimates of SDCBs do not deviate, in absolute value, more than 1 ns from their ground truth values published by the Centre for Orbit Determination in Europe.  相似文献   

8.
Estimation and analysis of Galileo differential code biases   总被引:1,自引:0,他引:1  
When sensing the Earth’s ionosphere using dual-frequency pseudorange observations of global navigation satellite systems (GNSS), the satellite and receiver differential code biases (DCBs) account for one of the main sources of error. For the Galileo system, limited knowledge is available about the determination and characteristic analysis of the satellite and receiver DCBs. To better understand the characteristics of satellite and receiver DCBs of Galileo, the IGGDCB (IGG, Institute of Geodesy and Geophysics, Wuhan, China) method is extended to estimate the satellite and receiver DCBs of Galileo, with the combined use of GPS and Galileo observations. The experimental data were collected from the Multi-GNSS Experiment network, covering the period of 2013–2015. The stability of both Galileo satellite and receiver DCBs over a time period of 36 months was thereby analyzed for the current state of the Galileo system. Good agreement of Galileo satellite DCBs is found between the IGGDCB-based DCB estimates and those from the German Aerospace Center (DLR), at the level of 0.22 ns. Moreover, high-level stability of the Galileo satellite DCB estimates is obtained over the selected time span (less than 0.25 ns in terms of standard deviation) by both IGGDCB and DLR algorithms. The Galileo receiver DCB estimates are also relatively stable for the case in which the receiver hardware device stays unchanged. It can also be concluded that the receiver DCB estimates are rather sensitive to the change of the firmware version and that the receiver antenna type has no great impact on receiver DCBs.  相似文献   

9.
The Global Positioning System (GPS) has become a powerful tool for ionospheric studies. In addition, ionospheric corrections are necessary for the augmentation systems required for Global Navigation Satellite Systems (GNSS) use. Dual-frequency carrier-phase and code-delay GPS observations are combined to obtain ionospheric observables related to the slant total electron content (sTEC) along the satellite-receiver line-of-sight (LoS). This observable is affected by inter-frequency biases [IFB; often called differential code biases (DCB)] due to the transmitting and the receiving hardware. These biases must be estimated and eliminated from the data in order to calibrate the experimental sTEC obtained from GPS observations. Based on the analysis of single differences of the ionospheric observations obtained from pairs of co-located dual-frequency GPS receivers, this research addresses two major issues: (1) assessing the errors translated from the code-delay to the carrier-phase ionospheric observable by the so-called levelling process, applied to reduce carrier-phase ambiguities from the data; and (2) assessing the short-term stability of receiver IFB. The conclusions achieved are: (1) the levelled carrier-phase ionospheric observable is affected by a systematic error, produced by code-delay multi-path through the levelling procedure; and (2) receiver IFB may experience significant changes during 1 day. The magnitude of both effects depends on the receiver/antenna configuration. Levelling errors found in this research vary from 1.4 total electron content units (TECU) to 5.3 TECU. In addition, intra-day vaiations of code-delay receiver IFB ranging from 1.4 to 8.8 TECU were detected.  相似文献   

10.
联合双频GPS数据,利用相位平滑伪距算法,可得到包含斜向电离层总电子含量(slant total electron content,sTEC)、测站和卫星差分码偏差(differential code bias,DCB)的电离层观测值(称之为"平滑伪距电离层观测值"),常应用于与电离层有关的研究。然而,平滑伪距电离层观测值易受平滑弧段长度和与测站有关的误差影响。提出一种新算法:利用非组合精密单点定位技术(precise point positioning,PPP)计算电离层观测值(称之为"PPP电离层观测值"),进而估计sTEC和站星DCB。基于短基线试验,先用一台接收机按上述两种方法估计sTEC,用于改正另一接收机观测值的电离层延迟以实施单频PPP,结果表明,利用PPP电离层观测值得到的sTEC精度较高,定位结果的可靠性较强。随后,选取全球分布的8个IGS(internationalGNSS service)连续跟踪站2009年1月内某四天的观测数据,利用上述两种电离层观测值计算所有卫星的DCB,并将计算结果与CODE发布的月平均值进行比较,其中,平滑伪距电离层观测值的卫星DCB估值与CODE(Centre for Orbit Deter mination in Europe)发布值的差别较大,部分卫星甚至可达0.2~0.3 ns,而PPP电离层观测值而言,绝大多数卫星对应的差异均在0.1 ns以内。  相似文献   

11.
Estimation and analysis of GPS satellite DCB based on LEO observations   总被引:1,自引:1,他引:0  
The Global Positioning System (GPS) satellite differential code bias (DCB) should be precisely calibrated when obtaining ionospheric slant total electron content (TEC). So far, it is ground-based GPS observations that have been used to estimate GPS satellite DCB. With the increased Low Earth Orbit (LEO) missions in the near future, the real-time satellite DCB estimation is a crucial factor in real-time LEO GPS data applications. One alternative way is estimating GPS DCB based on the LEO observations themselves, instead of using ground observations. We propose an approach to estimate the satellite DCB based on Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) and Challenging Minisatellite Payload (CHAMP) GPS observations during the years 2002–2012. The results have been validated through comparisons with those issued by Center for Orbit Determination in Europe (CODE). The evaluations indicate that: The approach can estimate satellite DCB in a reasonable way; the DCB estimated based on CHAMP observations is much better than those on COSMIC observations; the accuracy and precision of DCB show a possible dependency on the ionospheric ionization level. This method is significance for the real-time processing of LEO-based GNSS TEC data from the perspective of real-time applications.  相似文献   

12.
The global positioning system (GPS) differential code biases (DCB) provided by the International GNSS Service (IGS) show solar-cycle-like variation during 2002–2013. This study is to examine whether this variation of the GPS DCBs is associated with ionospheric variability. The GPS observations from low earth orbit (LEO) satellites including CHAMP, GRACE and Jason-1 are used to address this issue. The GPS DCBs estimated from the LEO-based observations at different orbit altitudes show a similar tendency as the IGS DCBs. However, this solar-cycle-like dependency is eliminated when the DCBs of 13 continuously operating GPS satellites are constrained to zero-mean. Our results thus revealed that ionospheric variation is not responsible for the long-term variation of the GPS DCBs. Instead, it is attributed to the GPS satellite replacement with different satellite types and the zero-mean condition imposed on all satellite DCBs.  相似文献   

13.
Multi-GNSS precise point positioning (MGPPP) using raw observations   总被引:5,自引:2,他引:3  
A joint-processing model for multi-GNSS (GPS, GLONASS, BDS and GALILEO) precise point positioning (PPP) is proposed, in which raw code and phase observations are used. In the proposed model, inter-system biases (ISBs) and GLONASS code inter-frequency biases (IFBs) are carefully considered, among which GLONASS code IFBs are modeled as a linear function of frequency numbers. To get the full rank function model, the unknowns are re-parameterized and the estimable slant ionospheric delays and ISBs/IFBs are derived and estimated simultaneously. One month of data in April, 2015 from 32 stations of the International GNSS Service (IGS) Multi-GNSS Experiment (MGEX) tracking network have been used to validate the proposed model. Preliminary results show that RMS values of the positioning errors (with respect to external double-difference solutions) for static/kinematic solutions (four systems) are 6.2 mm/2.1 cm (north), 6.0 mm/2.2 cm (east) and 9.3 mm/4.9 cm (up). One-day stabilities of the estimated ISBs described by STD values are 0.36 and 0.38 ns, for GLONASS and BDS, respectively. Significant ISB jumps are identified between adjacent days for all stations, which are caused by the different satellite clock datums in different days and for different systems. Unlike ISBs, the estimated GLONASS code IFBs are quite stable for all stations, with an average STD of 0.04 ns over a month. Single-difference experiment of short baseline shows that PPP ionospheric delays are more precise than traditional leveling ionospheric delays.  相似文献   

14.
全球导航卫星系统(Global Navigation Satellite System,GNSS)探测大气电离层需要精确处理由接收机差分码偏差(differential cade bias,DCB)引起的系统误差。准确掌握接收机DCB的多时间尺度精细变化等特性是联合美国GPS、中国北斗卫星导航系统(BeiDou navigation satellite system,BDS)和欧盟Galileo等多GNSS技术监测电离层所面临的主要科学问题之一。为此,提出了基于零基线精密估计站间单差接收机DCB的方法,并对站间单差接收机DCB的日加权平均值进行了分析。基于4台多模接收机采集于2013年的双频观测值,揭示了站间单差接收机DCB的变化可能受3种因素的影响,即接收机内置软件的版本升级(实验中引起了约3 ns的显著增加)、拆卸个别接收机所导致的观测条件改变(实验中引起了约1.3 ns的显著减少)和估计方法的误差(引起了与导航系统卫星几何结构重复性相一致的周期性变化)等。  相似文献   

15.
Global navigation satellite systems (GNSS) have been widely used to monitor variations in the earth’s ionosphere by estimating total electron content (TEC) using dual-frequency observations. Differential code biases (DCBs) are one of the important error sources in estimating precise TEC from GNSS data. The International GNSS Service (IGS) Analysis Centers have routinely provided DCB estimates for GNSS satellites and IGS ground receivers, but the DCBs for regional and local network receivers are not provided. Furthermore, the DCB values of GNSS satellites or receivers are assumed to be constant over 1?day or 1?month, which is not always the case. We describe Matlab code to estimate GNSS satellite and receiver DCBs for time intervals from hours to days; the software is called M_DCB. The DCBs of GNSS satellites and ground receivers are tested and evaluated using data from the IGS GNSS network. The estimates from M_DCB show good agreement with the IGS Analysis Centers with a mean difference of less than 0.7?ns and an RMS of less than 0.4?ns, even for a single station DCB estimate.  相似文献   

16.
Global Positioning System (GPS) total electron content (TEC) measurements, although highly precise, are often rendered inaccurate due to satellite and receiver differential code biases (DCBs). Calculated satellite DCB values are now available from a variety of sources, but receiver DCBs generally remain an undertaking of receiver operators and processing centers. A procedure for removing these receiver DCBs from GPS-derived ionospheric TEC at high latitudes, using Canadian Advanced Digital Ionosonde (CADI) measurements, is presented. Here, we will test the applicability of common numerical methods for estimating receiver DCBs in high-latitude regions and compare our CADI-calibrated GPS vertical TEC (vTEC) measurements to corresponding International GNSS Service IONEX-interpolated vTEC map data. We demonstrate that the bias values determined using the CADI method are largely independent of the topside model (exponential, Epstein, and α-Chapman) used. We further confirm our results via comparing bias-calibrated GPS vTEC with those derived from incoherent scatter radar (ISR) measurements. These CADI method results are found to be within 1.0 TEC units (TECU) of ISR measurements. The numerical methods tested demonstrate agreement varying from within 1.6 TECU to in excess of 6.0 TECU when compared to ISR measurements.  相似文献   

17.
接收机端伪距偏差是指非理想的卫星导航信号在接收机前端带宽和相关器间隔不同时产生的伪距测量系统性偏差。研究表明,北斗二号、GPS和Galileo系统均存在与接收机类型相关的伪距偏差,影响基于混合类型接收机站网的精密数据处理。本文基于iGMAS网和MGEX网观测数据,采用MW组合、伪距残差和伪距无几何距离无电离层组合3种方法分析北斗三号接收机端伪距偏差特性。试验结果表明,北斗三号同样存在与接收机类型相关的伪距偏差,且无电离层组合的伪距偏差可以达到6 ns。根据偏差特性,按接收机类型建立了8类伪距偏差改正模型。将上述模型应用于卫星差分码偏差(DCB)估计与单频伪距单点定位,结果表明,模型改正后可以显著提升不同接收机类型估计的卫星DCB一致性,其中基于iGMAS网和MGEX网两个不同接收机站网估计得到的北斗三号C2I-C6I、C1P-C5P和C2I-C7D DCB差值分别平均降低了91.6%、64.7%和71.9%;模型改正后单频伪距单点定位水平方向和高程方向精度分别提升了13.9%和11.0%。  相似文献   

18.
A. El-Mowafy 《GPS Solutions》2014,18(4):553-561
A method is presented for real-time validation of GNSS measurements of a single receiver, where data from each satellite are independently processed. A geometry-free observation model is used with a reparameterized form of the unknowns to overcome rank deficiency of the model. The ionosphere error and non-constant biases such as multipath are assumed changing relatively smoothly as a function of time. Data validation and detection of errors are based on statistical testing of the observation residuals using the detection–identification–adaptation approach. The method is applicable to any GNSS with any number of frequencies. The performance of validation method was evaluated using multi-frequency data from three GNSS (GPS, GLONASS, and Galileo) that span 3 days in a test site at Curtin University, Australia. Performance of the method in detection and identification of outliers in code observations, and detection of cycle slips in phase data were examined. Results show that the success rate vary according to precision of observations and their number as well as size of the errors. The method capability is demonstrated when processing four IOV Galileo satellites in a single-point-positioning mode and in another test by comparing its performance with Bernese software in detection of cycle slips in precise point-positioning processing using GPS data.  相似文献   

19.
A receiver hardware delay should be seriously considered for time-transfer and determination of ionospheric delay corrections for wide area differential GPS positioning. A receiver hardware delay does not generally effect the common geo-position application, as suitable differences of observations are used, or equivalently, clock error parameters are introduced, epoch-wise, that also absorb the delays. This paper investigates the behavior of inter-frequency (or observation-type) receiver hardware delays by using a single difference (SD) model, which estimates the receiver delay along with the receiver clock error (and SD ambiguities of a reference satellite with carrier phase observations) for zero and short baselines. The purpose of this paper is to model the between-observation-type delays for the purpose of precise positioning, under practical circumstances. The focus is on data series of differential SD receiver clock biases, since they reflect the behavior of receiver hardware delays with time. A simple linear regression of the data series is employed to study the behavior, and test statistics are employed to assess both the significance of the parameters and the observations fit for the linear regression. The statistical analysis results indicate that almost all inter-observation type receiver delays can be modeled as the sum of a constant (offset) and a constant rate of change (slope). The analysis shows that the differential receiver delay is generally at the mm- to cm-level on phase, while at the dm-level on code for the equipment used in the experiments.  相似文献   

20.
Compared with the traditional GPS L1 C/A BPSK-R(1) signal, wideband global navigation satellite system (GNSS) signals suffer more severe distortion due to ionospheric dispersion. Ionospheric dispersion inevitably introduces additional errors in pseudorange and carrier phase observations that cannot be readily eliminated by traditional methods. Researchers have reported power losses, waveform ripples, correlation peak asymmetries, and carrier phase shifts caused by ionospheric dispersion. We analyze the code tracking bias induced by ionospheric dispersion and propose an efficient all-pass filter to compensate the corresponding nonlinear group delay over the signal bandwidth. The filter is constructed in a cascaded biquad form based on the estimated total electron content (TEC). The effects of TEC accuracy, filter order, and fraction parameter on the filter fitting error are explored. Taking the AltBOC(15,10) signal as an example, we compare the time domain signal waveforms, correlation peaks, code tracking biases, and carrier phase biases with and without this all-pass filter and demonstrate that the proposed delay-equalization all-pass filter is a potential solution to ionospheric dispersion compensation and mitigation of observation biases for wideband GNSS signals.  相似文献   

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