Determination of the Differential Code Bias for Current BDS Satellites

The differential code bias (DCB) in global navigation satellite system (GNSS) satellites should be precisely determined using real ground GNSS data when designing certain applications, such as ionospheric remote sensing, precise positioning, and timing. Different from GPS with a full constellation, the number of BDS (BeiDou Satellite System developed by China) satellites currently in orbit is very limited, and the data from BDS are insufficient for estimating satellite DCB simultaneously with ionospheric total-electron-content modeling. In view of this, a calibration approach, namely, GPS-aided DCB determination (GPSADCB), is proposed to estimate the DCB of current BDS satellites with the aid of GPS data. The data from GPS are used to derive the ionospheric delay along the propagation path of the BDS signal. Before applying GPSADCB to estimate the DCB of current BDS satellites, the performance of this approach is first validated using two sets of GPS data in a simulated BDS case. Then, a continuous four-day data set gathered by two BDS receivers is used to determine the DCB of current BDS satellites based on GPSADCB. Validation results indicate that the difference of DCB estimates between GPSADCB and the Center for Orbit Determination in Europe is about 0.3 ns and the stability of DCB estimates in one month is about 0.2 ns. The DCB of different BDS satellites ranges from -10 ns to 13 ns, and the mean of day-to-day scatter for DCB estimates is below 0.2 ns over the period of data collection. It is demonstrated that the proposed approach can be used to estimate BDS satellite DCB at the initial stage with a few satellites in orbit.

[1]  E. Sardón,et al.  Estimation of total electron content using GPS data: How stable are the differential satellite and receiver instrumental biases? , 1997 .

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

[3]  Todd Walter,et al.  Modified Ionospheric Correction Algorithm for the SBAS Based on Geometry Monitor Concept , 2005 .

[4]  J. Kouba.  A GUIDE TO USING INTERNATIONAL GNSS SERVICE (IGS) PRODUCTS , 2003 .

[5]  Debao Wen,et al.  Tomographic reconstruction of ionospheric electron density based on constrained algebraic reconstruction technique , 2010 .

[6]  O. Ovstedal,et al.  Absolute Positioning with Single-Frequency GPS Receivers , 2002 .

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

[8]  Jaume Sanz,et al.  Global observation of the ionospheric electronic response to solar events using ground and LEO GPS data , 1998 .

[9]  B. Wilson,et al.  Instrumental Biases in Ionospheric Measurements Derived from GPS Data , 1993 .

[10]  Jaume Sanz Subirana,et al.  Feasibility of wide-area subdecimeter navigation with GALILEO and Modernized GPS , 2003, IEEE Trans. Geosci. Remote. Sens..

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

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

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

[14]  Zishen Li,et al.  Two-step method for the determination of the differential code biases of COMPASS satellites , 2012, Journal of Geodesy.

[15]  Yunbin Yuan,et al.  A generalized trigonometric series function model for determining ionospheric delay , 2004 .

[16]  S. Schlüter,et al.  GPS/GLONASS-based TEC measurements as a contributor for space weather forecast , 2002 .

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

[18]  Ashish K. Shukla,et al.  Two-Shell Ionospheric Model for Indian Region: A Novel Approach , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Ola Øvstedal,et al.  Absolute Positioning with Single-Frequency GPS Receivers , 2002, GPS Solutions.

[20]  G. Sasibhushana Rao,et al.  GPS satellite and receiver instrumental biases estimation using least squares method for accurate ionosphere modelling , 2007 .

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

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

[23]  Zuo Xiao,et al.  Accuracy analysis of the GPS instrumental bias estimated from observations in middle and low latitudes , 2010 .

[24]  Richard B. Langley,et al.  Dual-frequency GPS Precise Point Positioning with WADGPS Corrections , 2005 .

[25]  Manuel Hernández-Pajares,et al.  IGS Ionosphere WG Status Report : Performance of IGS Ionosphere TEC Maps-Position Paper - , 2004 .

[26]  Yunbin Yuan,et al.  The ionospheric eclipse factor method (IEFM) and its application to determining the ionospheric delay for GPS , 2008 .

[27]  K. Ramalingam,et al.  GPS satellite and receiver instrumental biases estimation using SVD algorithm , 2008, IEEE Transactions on Aerospace and Electronic Systems.

[28]  R. Grenfell,et al.  Refining the Klobuchar ionospheric coefficients based on GPS observations , 2008, IEEE Transactions on Aerospace and Electronic Systems.

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

[30]  Yunbin Yuan,et al.  Ionospheric Response to the Geomagnetic Storm on August 21, 2003 Over China Using GNSS-Based Tomographic Technique , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[31]  Christian Tiberius,et al.  Single-frequency precise point positioning with optimal filtering , 2006 .

[32]  Judah Levine,et al.  A review of time and frequency transfer methods , 2008 .

[33]  Yuei-An Liou,et al.  Identification of Inclined Ionospheric Layers Using Analysis of GPS Occultation Data , 2011, IEEE Transactions on Geoscience and Remote Sensing.