Correlation between Ionospheric TEC and the DCB Stability of GNSS Receivers from 2014 to 2016

The Global Navigation Satellite System (GNSS) differential code biases (DCBs) are a major obstacle in estimating the ionospheric total electron content (TEC). The DCBs of the GNSS receiver (rDCBs) are affected by various factors such as data quality, estimation method, receiver type, hardware temperature, and antenna characteristics. This study investigates the relationship between TEC and rDCB, and TEC and rDCB stability during a three-year period from 2014 to 2016. Linear correlations between pairs of variables, measured with Pearson’s coefficient (R), are considered. It is shown that the correlation between TEC and rDCB is the smallest in low-latitude regions. The mid-latitude regions exhibit the maximum value of R. In contrast, the correlation between TEC and rDCB root mean square (RMS, stability) was greater in low-latitude regions. A strong positive correlation (R ≥ 0.90) on average between TEC and rDCB RMS was also revealed at two additional GNSS stations in low-latitude regions, where the correlation shows clear latitudinal dependency. We found that the correlation between TEC and rDCB stability is still very strong even after replacing a GNSS receiver.

[1]  Andrew B. Christensen,et al.  Features of annual and semiannual variations derived from the global ionospheric maps of total electron content , 2007 .

[2]  Richard B. Langley,et al.  The nature of GPS differential receiver bias variability: An examination in the polar cap region , 2015 .

[3]  Pawel Wielgosz,et al.  Regional Ionosphere Mapping with Kriging and Multiquadric Methods , 2003 .

[4]  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.

[5]  Claudio Brunini,et al.  Accuracy assessment of the GPS-TEC calibration constants by means of a simulation technique , 2011 .

[6]  S. Kao,et al.  Factors affecting the estimation of GPS receiver instrumental biases , 2013 .

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

[8]  Charles S. Carrano,et al.  Comparison of equatorial GPS-TEC observations over an African station and an American station during the minimum and ascending phases of solar cycle 24 , 2013 .

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

[10]  Andrew J. Mazzella,et al.  Plasmasphere effects for GPS TEC measurements in North America , 2009 .

[11]  Jinyun Guo,et al.  Temporal-Spatial Variation of Global GPS-Derived Total Electron Content, 1999–2013 , 2015, PloS one.

[12]  Peter Teunissen,et al.  Characterization of multi-GNSS between-receiver differential code biases using zero and short baselines , 2015 .

[13]  Wei Zhang,et al.  The variation of the estimated GPS instrumental bias and its possible connection with ionospheric variability , 2014 .

[14]  Xiaoqing Pi,et al.  Assessment of global TEC mapping using a three-dimensional electron density model , 1999 .

[15]  Christa Boer,et al.  Correlation Coefficients: Appropriate Use and Interpretation , 2018, Anesthesia and analgesia.

[16]  Brian Wilson,et al.  Extracting Ionospheric Measurements from GPS in the Presence of Anti-Spoofing , 1994 .

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

[18]  Leos Mervart,et al.  Global and regional ionosphere models using the GPS double difference phase observable , 1996 .

[19]  Wei Zhang,et al.  The influence of geomagnetic storms on the estimation of GPS instrumental biases , 2009 .

[20]  Maxim Keshin,et al.  A new algorithm for single receiver DCB estimation using IGS TEC maps , 2012, GPS Solutions.

[21]  Artem M. Padokhin,et al.  Influence of GPS/GLONASS differential code biases on the determination accuracy of the absolute total electron content in the ionosphere , 2015, Geomagnetism and Aeronomy.

[22]  René Warnant,et al.  Reliability of the TEC Computed Using GPS Measurements — The Problem of Hardware Biases , 1997, Acta Geodaetica et Geophysica Hungarica.

[23]  Sang Jeong Lee,et al.  The influence of grounding on GPS receiver differential code biases , 2018, Advances in Space Research.

[24]  Allan T. Weatherwax,et al.  Accuracy of GPS total electron content: GPS receiver bias temperature dependence , 2013 .

[25]  Takuya Tsugawa,et al.  A new technique for mapping of total electron content using GPS network in Japan , 2002 .

[26]  James R. Clynch,et al.  Variability of GPS satellite differential group delay biases , 1991 .

[27]  A. Rius,et al.  Estimation of the transmitter and receiver differential biases and the ionospheric total electron content from Global Positioning System observations , 1994 .

[28]  Baocheng Zhang,et al.  On the short-term temporal variations of GNSS receiver differential phase biases , 2017, Journal of Geodesy.

[29]  Chris Rizos,et al.  The International GNSS Service in a changing landscape of Global Navigation Satellite Systems , 2009 .

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

[31]  Takashi Maruyama,et al.  Determination of GPS receiver differential biases by neural network parameter estimation method , 2005 .