On the application of the raw-observation-based PPP to global ionosphere VTEC modeling: an advantage demonstration in the multi-frequency and multi-GNSS context

The ionospheric delay accounts for one of the major errors that the Global Navigation Satellite Systems (GNSS) suffer from. Hence, the global ionosphere Vertical Total Electron Content (VTEC) map has been an important atmospheric product within the International GNSS Service (IGS) since its early establishment. In this contribution, an enhanced method has been proposed for the modeling of the global VTECs, in which the enhancements include two aspects. Firstly, to cope with the rapid development of the newly established Galileo and BeiDou constellations in recent years, we extend the current dual-system (GPS/GLONASS) solution to a quad-system (GPS/GLONASS/Galileo/BeiDou) solution. More importantly, instead of using dual-frequency observations based on the Carrier-to-Code Leveling method, all available triple-frequency signals are utilized with a general raw-observation-based multi-frequency Precise Point Positioning model, which can process dual-, triple- or even arbitrary-frequency observations compatibly and flexibly. Benefiting from this, quad-system slant ionospheric delays can be retrieved based on multi-frequency observations in a more flexible, accurate and reliable way, which are finally used to establish global VTEC models with the spherical harmonic function. In this process, multi-GNSS Differential Code Biases (DCBs) are also estimated as by-products. More than 400 globally distributed stations from the IGS and the Multi-GNSS Experiment (MGEX) networks have been processed in both 2014 (with high solar activity) and 2018 (with low solar activity). Global VTECs have been compared with the IGS final products, and the over-ocean VTECs are validated with the results from the JASON altimeter. The mean RMS values of the VTEC differences are 1.84 (2014) and 1.23 (2018) TECUs with respect to the IGS final products. The standard deviations of the VTEC differences with respect to the JASON results are 4.71 (2014) and 2.82 (2018) TECUs, outperforming all the other products generated with the spherical harmonic function. Additionally, multi-GNSS satellite DCBs have also been validated with the existing products from the Center for Orbit Determination in Europe and MGEX. All the results prove that the proposed method can be used as an effective and accurate approach for global VTEC modeling and DCB estimation, especially in the future multi-frequency and multi-GNSS context.

[1]  Ruizhi Chen,et al.  Spherical cap harmonic model for mapping and predicting regional TEC , 2011 .

[2]  Manuel Hernández-Pajares,et al.  The ionosphere: effects, GPS modeling and the benefits for space geodetic techniques , 2011 .

[3]  Rolf Dach,et al.  CODE’s five-system orbit and clock solution—the challenges of multi-GNSS data analysis , 2017, Journal of Geodesy.

[4]  Jinling Wang,et al.  Assessment of precise orbit and clock products for Galileo, BeiDou, and QZSS from IGS Multi-GNSS Experiment (MGEX) , 2016, GPS Solutions.

[5]  S. Schaer Mapping and predicting the Earth's ionosphere using the Global Positioning System. , 1999 .

[6]  Baocheng Zhang,et al.  Multi-GNSS triple-frequency differential code bias (DCB) determination with precise point positioning (PPP) , 2018, Journal of Geodesy.

[7]  A. Garcia-Rigo,et al.  The IGS VTEC maps: a reliable source of ionospheric information since 1998 , 2009 .

[8]  Y. Bock,et al.  Triple-frequency GPS precise point positioning with rapid ambiguity resolution , 2013, Journal of Geodesy.

[9]  Baocheng Zhang,et al.  Three methods to retrieve slant total electron content measurements from ground‐based GPS receivers and performance assessment , 2016 .

[10]  Baocheng Zhang,et al.  Joint estimation of vertical total electron content (VTEC) and satellite differential code biases (SDCBs) using low-cost receivers , 2018, Journal of Geodesy.

[11]  Jaume Sanz,et al.  New approaches in global ionospheric determination using ground GPS data , 1999 .

[12]  R. Dach,et al.  Bernese GNSS Software Version 5.2 , 2015 .

[13]  Torsten Mayer-Gürr,et al.  Processing of GNSS constellations and ground station networks using the raw observation approach , 2018, Journal of Geodesy.

[14]  Jaume Sanz,et al.  Improvement of global ionospheric VTEC maps by using kriging interpolation technique , 2005 .

[15]  Orhan Arikan,et al.  Investigation of total electron content variability due to seismic and geomagnetic disturbances in the ionosphere , 2010 .

[16]  Sandro M. Radicella,et al.  Calibration errors on experimental slant total electron content (TEC) determined with GPS , 2007 .

[17]  Harald Schuh,et al.  Refining ionospheric delay modeling for undifferenced and uncombined GNSS data processing , 2018, Journal of Geodesy.

[18]  Peter Steigenberger,et al.  Differential Code Bias Estimation using Multi‐GNSS Observations and Global Ionosphere Maps , 2014 .

[19]  Peter Steigenberger,et al.  The Multi-GNSS Experiment (MGEX) of the International GNSS Service (IGS) - Achievements, prospects and challenges , 2017 .

[20]  O. Montenbruck,et al.  IGS-MGEX: Preparing the Ground for Multi-Constellation GNSS Science , 2013 .

[21]  Yidong Lou,et al.  An improved approach to model ionospheric delays for single-frequency Precise Point Positioning , 2012 .

[22]  Jing-nan Liu,et al.  GPS inter-frequency clock bias estimation for both uncombined and ionospheric-free combined triple-frequency precise point positioning , 2018, Journal of Geodesy.

[23]  Oliver Montenbruck,et al.  Determination of differential code biases with multi-GNSS observations , 2016, Journal of Geodesy.

[24]  Ningbo Wang,et al.  SHPTS: towards a new method for generating precise global ionospheric TEC map based on spherical harmonic and generalized trigonometric series functions , 2015, Journal of Geodesy.

[25]  Baocheng Zhang,et al.  Real-Time Precise Point Positioning (RTPPP) with raw observations and its application in real-time regional ionospheric VTEC modeling , 2018, Journal of Geodesy.

[26]  Attila Komjathy,et al.  Global ionospheric total electron content mapping using the global positioning system , 1997 .

[27]  Baocheng Zhang,et al.  Multi-GNSS precise point positioning (MGPPP) using raw observations , 2017, Journal of Geodesy.

[28]  Ningbo Wang,et al.  Performance of various predicted GNSS global ionospheric maps relative to GPS and JASON TEC data , 2018, GPS Solutions.

[29]  Qian Wu,et al.  Ionosphere response to solar wind high‐speed streams , 2008 .

[30]  Baocheng Zhang,et al.  GLONASS pseudorange inter-channel biases considerations when jointly estimating GPS and GLONASS clock offset , 2017, GPS Solutions.

[31]  J. Klobuchar Ionospheric Time-Delay Algorithm for Single-Frequency GPS Users , 1987, IEEE Transactions on Aerospace and Electronic Systems.

[32]  Joachim Feltens,et al.  The activities of the Ionosphere Working Group of the International GPS Service (IGS) , 2003 .

[33]  Baocheng Zhang,et al.  On the estimability of parameters in undifferenced, uncombined GNSS network and PPP-RTK user models by means of $$\mathcal {S}$$S-system theory , 2016 .

[34]  Peter Steigenberger,et al.  Estimation of satellite antenna phase center offsets for Galileo , 2016, Journal of Geodesy.

[35]  Anthony J. Mannucci,et al.  Automated daily processing of more than 1000 ground‐based GPS receivers for studying intense ionospheric storms , 2005 .

[36]  D. Odijk Fast precise GPS positioning in the presence of ionospheric delays , 2002 .

[37]  Andrzej Krankowski,et al.  Methodology and consistency of slant and vertical assessments for ionospheric electron content models , 2017, Journal of Geodesy.

[38]  Chuang Shi,et al.  Consistency of seven different GNSS global ionospheric mapping techniques during one solar cycle , 2018, Journal of Geodesy.

[39]  Andrew Simsky,et al.  Origin and Compensation of GLONASS Inter-frequency Carrier Phase Biases in GNSS Receivers , 2012 .

[40]  Baocheng Zhang,et al.  PPP-RTK based on undifferenced and uncombined observations: theoretical and practical aspects , 2018, Journal of Geodesy.

[41]  Paul Collins,et al.  Global and Regional Ionospheric Corrections for Faster PPP Convergence , 2014 .

[42]  Anthony J. Mannucci,et al.  A global mapping technique for GPS‐derived ionospheric total electron content measurements , 1998 .

[43]  J. McCallum,et al.  Same‐beam VLBI observations of SELENE for improving lunar gravity field model , 2010 .