Modelling short-term variations of differential code bias aiding in extraction of ionospheric observables with sparse kernel learning

The timing group delay parameter (TGD) or differential code bias parameter (DCB) is an important factor that affects the performance of GNSS basic services; therefore, TGD and DCB must be taken seriously. Moreover, the TGD parameter is modulated in the navigation message, taking into account the impact of TGD on the performance of the basic service. International GNSS Monitoring and Assessment System (iGMAS) provides the broadcast ephemeris with TGD parameter and the Chinese Academy of Science (CAS) provides DCB products. In this paper, the current available BDS-3 TGD and DCB parameters are firstly described in detail, and the relationship of TGD and DCB for BDS-3 is figured out. Then, correction models of BDS-3 TGD and DCB in standard point positioning (SPP) or precise point positioning (PPP) are given, which can be applied in various situations. For the effects of TGD and DCB in the SPP and PPP solution processes, all the signals from BDS-3 were researched, and the validity of TGD and DCB has been further verified. The experimental results show that the accuracy of B1I, B1C and B2a single-frequency SPP with TGD or DCB correction was improved by approximately 12–60%. TGD will not be considered for B3I single-frequency, because the broadcast satellite clock offset is based on the B3I as the reference signal. The positioning accuracy of B1I/B3I and B1C/B2a dual-frequency SPP showed that the improvement range for horizontal components is 60.2% to 74.4%, and the vertical components improved by about 50% after the modification of TGD and DCB. In addition, most of the uncorrected code biases are mostly absorbed into the receiver clock bias and other parameters for PPP, resulting in longer convergence time. The convergence time can be max increased by up to 50% when the DCB parameters are corrected. Consequently, the positioning accuracy can reach the centimeter level after convergence, but it is critical for PPP convergence time and receiver clock bias that the TGD and DCB correction be considered seriously.

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Estimation and analysis of GNSS receiver differential code bias in Southeast Asia using a new method

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/799/1/012023 ◽

2021 ◽

Vol 799 (1) ◽

pp. 012023

Author(s):

Qisheng Wang ◽

Shuanggen Jin ◽

Youjian Hu

Keyword(s):

Southeast Asia ◽

New Method ◽

Differential Code Bias ◽

Gnss Receiver ◽

Code Bias

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Performance Analysis of GPS/BDS Precise Point Positioning

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.713-715.1123 ◽

2015 ◽

Vol 713-715 ◽

pp. 1123-1126

Author(s):

Xiao Yu Li ◽

Jun Wang ◽

Ya Tao Liu

Keyword(s):

Precise Point Positioning ◽

Satellite Orbit ◽

Gps Measurements ◽

Differential Code Bias ◽

Phase Offset ◽

Antenna Phase ◽

Offset Correction ◽

Code Bias ◽

Point Positioning ◽

Processing Steps

Precise Point Positioning (PPP) with GPS measurements has achieved a level of success. In order to benefit from the multiple available constellations, research has been undertaken to combineGPS and BDS measurements in PPP processing.Mathematical models of GPS/BDS combined precise point positioning are introduced in this paper. GPS/BDS combined PPP models are developed based on the GPS-only PPP. The data pre-processing steps include applying satellite orbit and clock corrections, satellite antenna phase offset correction, receiver antenna phase offset correction, differential code bias corrections, troposphere delay corrections and the the Ionosphere-free observation combination is used. The results show that the positioning precision and convergence speed of GPS/BDS combined PPP are improved compared with GPS-only PPP.

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Assessment of BeiDou differential code bias variations from multi-GNSS network observations

Annales Geophysicae ◽

10.5194/angeo-34-259-2016 ◽

2016 ◽

Vol 34 (2) ◽

pp. 259-269 ◽

Cited By ~ 67

Author(s):

S. G. Jin ◽

R. Jin ◽

D. Li

Keyword(s):

Orbital Plane ◽

Satellite Orbit ◽

Satellite System ◽

Global Navigation Satellite Systems ◽

Dominant Factor ◽

Earth Orbit ◽

Navigation Satellite ◽

Differential Code Bias ◽

Code Bias ◽

Gnss Network

Abstract. The differential code bias (DCB) of global navigation satellite systems (GNSSs) affects precise ionospheric modeling and applications. In this paper, daily DCBs of the BeiDou Navigation Satellite System (BDS) are estimated and investigated from 2-year multi-GNSS network observations (2013–2014) based on global ionospheric maps (GIMs) from the Center for Orbit Determination in Europe (CODE), which are compared with Global Positioning System (GPS) results. The DCB of BDS satellites is a little less stable than GPS solutions, especially for geostationary Earth orbit (GEO) satellites. The BDS GEO observations decrease the precision of inclined geosynchronous satellite orbit (IGSO) and medium Earth orbit (MEO) DCB estimations. The RMS of BDS satellites DCB decreases to about 0.2 ns when we remove BDS GEO observations. Zero-mean condition effects are not the dominant factor for the higher RMS of BDS satellites DCB. Although there are no obvious secular variations in the DCB time series, sub-nanosecond variations are visible for both BDS and GPS satellites DCBs during 2013–2014. For satellites in the same orbital plane, their DCB variations have similar characteristics. In addition, variations in receivers DCB in the same region are found with a similar pattern between BDS and GPS. These variations in both GPS and BDS DCBs are mainly related to the estimated error from ionospheric variability, while the BDS DCB intrinsic variation is in sub-nanoseconds.

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Influence of the GLONASS inter-frequency bias on differential code bias estimation and ionospheric modeling

GPS Solutions ◽

10.1007/s10291-017-0618-5 ◽

2017 ◽

Vol 21 (3) ◽

pp. 1355-1367 ◽

Cited By ~ 9

Author(s):

Xiaohong Zhang ◽

Weiliang Xie ◽

Xiaodong Ren ◽

Xingxing Li ◽

Keke Zhang ◽

...

Keyword(s):

Bias Estimation ◽

Differential Code Bias ◽

Ionospheric Modeling ◽

Code Bias

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Investigation and Validation of the Time-Varying Characteristic for the GPS Differential Code Bias

Remote Sensing ◽

10.3390/rs11040428 ◽

2019 ◽

Vol 11 (4) ◽

pp. 428 ◽

Cited By ~ 6

Author(s):

Haojun Li ◽

Jingxin Xiao ◽

Weidong Zhu

Keyword(s):

Single Point ◽

Time Varying ◽

International Gnss Service ◽

Data Set ◽

Differential Code Bias ◽

Triple Frequency ◽

Code Bias ◽

Constant Part ◽

The Difference ◽

Better Than

The time-varying characteristic of the bias in the GPS code observation is investigated using triple-frequency observations. The method for estimating the combined code bias is presented and the twelve-month (1 January–31 December 2016) triple-frequency GPS data set from 114 International GNSS Service (IGS) stations is processed to analyze the characteristic of the combined code bias. The results show that the main periods of the combined code bias are 12, 8, 6, 4, 4.8 and 2.67 h. The time-varying characteristic of the combined code bias, which is the combination of differential code bias (DCB) (P1–P5) and DCB (P1–P2), shows that the real satellite DCBs are also time-varying. The difference between the two sets of the computed constant parts of the combined code bias, with the IGS DCB products of DCB (P1–P2) and DCB (P1–P2) and the mean of the estimated 24-h combined code bias series, further show that the combined code bias cannot be replaced by the DCB (P1–P2) and DCB (P1–P5) products. The time-varying part of inter-frequency clock bias (IFCB) can be estimated by the phase and code observations and the phase based IFCB is the combinations of the triple-frequency satellite uncalibrated phase delays (UPDs) and the code-based IFCB is the function of the DCBs. The performances of the computed the IFCB with different methods in single point positioning indicate that the accuracy for the constant part of the combined code bias is reduced, when the IGS DCB products are used to compute. These performances also show that the time-varying part of IFCB estimated with phase observation is better than that of code observation. The predicted results show that 98% of the predicted constant part of the combined code bias can be corrected and the attenuation of the predicted accuracy is much less evident. However, the accuracy of the predicted time-varying part decreases significantly with the predicted time.

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