Optimization of ground tracking stations for BDS-3 satellite orbit determination

Abstract A precise satellite orbit is the basis for high-precision services for users, and the determination of high-precision satellite orbits depends on the reasonable distribution and volume of ground tracking stations (GTSs). In July 2020, the BeiDou global navigation satellite system (BDS-3) was completed and began to be operated globally. Based on the principle of dynamic orbit determination, we first developed an algorithm to determine the optimal distribution and number of GTSs for accurate satellite orbit determination. Subsequently, based on 10 GTSs located in China, the optimal distribution and number of GTSs with and without inter-satellite link (ISL) ranging observations were determined. Finally, real measurements of GTS and ISL ranging observation data were used to validate the GTS results yielded by the algorithm. Using 18 BDS-3 satellites, and based on non-ISL observations and 10 Chinese regional GTSs, we found that GTSs distributed near the equator contributed significantly to the accuracy of orbit determination for these satellites compared to other GTSs. Orbit determination results obtained from the measured data of the optimal GTSs were more accurate than those obtained from the measured data of uniformly distributed global GTSs. Upon the addition of 55 uniformly distributed GTSs worldwide, the orbit determination accuracy for BDS-3 satellites tended to plateau. Moreover, following the addition of ISL, although the distribution and number of GTSs was optimized using the proposed algorithm, the orbit determination results from the measured data revealed that a change in the distribution and number of GTSs had a limited effect on the BDS-3 orbit determination results.

[1]  J. Kusche,et al.  Regularization of geopotential determination from satellite data by variance components , 2002 .

[2]  Ralf Schmid,et al.  IGS14/igs14.atx: a new framework for the IGS products , 2016 .

[3]  Feng Zhang,et al.  Precise orbit determination for BDS-3 satellites using satellite-ground and inter-satellite link observations , 2019, GPS Solutions.

[4]  Leos Mervart,et al.  Efficient satellite orbit modelling using pseudo-stochastic parameters , 2006 .

[5]  H. Schuh,et al.  Global Mapping Function (GMF): A new empirical mapping function based on numerical weather model data , 2006 .

[6]  O. Francis,et al.  Modelling the global ocean tides: modern insights from FES2004 , 2006 .

[7]  Chengpan Tang,et al.  Inter-Satellite Link Enhanced Orbit Determination for BeiDou-3 , 2019, Journal of navigation.

[8]  Junyi Xu,et al.  Generalised DOPs with Consideration of the Influence Function of Signal-in-Space Errors , 2011, Journal of Navigation.

[9]  Jean-Charles Marty,et al.  A new combined global gravity field model including GOCE data from the collaboration of GFZ Potsdam and GRGS Toulouse , 2010 .

[10]  Yufeng Yang,et al.  BDS satellite clock offset prediction based on a semiparametric adjustment model considering model errors , 2020, Satellite Navigation.

[11]  Rui Zhang,et al.  Contribution analysis of inter-satellite ranging observation to BDS-2 satellite orbit determination based on regional tracking stations , 2019, Acta Astronautica.

[12]  Jinlong Li,et al.  Progress and performance evaluation of BeiDou global navigation satellite system: Data analysis based on BDS-3 demonstration system , 2018, Science China Earth Sciences.

[13]  Haibo He,et al.  Preliminary assessment of the navigation and positioning performance of BeiDou regional navigation satellite system , 2013, Science China Earth Sciences.

[14]  C. Bizouard,et al.  The Combined Solution C04 for Earth Orientation Parameters Consistent with International Terrestrial Reference Frame 2005 , 2009 .

[15]  J. Zumberge,et al.  Precise point positioning for the efficient and robust analysis of GPS data from large networks , 1997 .

[16]  Yue Mao,et al.  Basic performance and future developments of BeiDou global navigation satellite system , 2020 .

[17]  J. Saastamoinen.  Atmospheric Correction for the Troposphere and Stratosphere in Radio Ranging Satellites , 2013 .

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

[19]  Laiping Feng,et al.  Monitoring and Assessment of GNSS Open Services , 2011, Journal of Navigation.

[20]  L. Mervart,et al.  Extended orbit modeling techniques at the CODE processing center of the international GPS service for geodynamics (IGS): theory and initial results , 1994, manuscripta geodaetica.

[21]  Yang Yuan-xi.  Integrated Navigation by Using Variance Component Estimates of Multi-sensor Measurements and Adaptive Weights of Dynamic Model Information , 2004 .

[22]  H. Schuh,et al.  Short Note: A global model of pressure and temperature for geodetic applications , 2007 .

[23]  G. Beutler,et al.  A New Solar Radiation Pressure Model for GPS Satellites , 1999, GPS Solutions.

[24]  Gerd Gendt,et al.  Improving carrier-phase ambiguity resolution in global GPS network solutions , 2005 .

[25]  Zhang Wei-xing,et al.  Influence of Ground Station Number and its Geographical Distribution on Combined Orbit Determination of Navigation Satellite , 2011 .

[26]  O. Montenbruck,et al.  Enhanced solar radiation pressure modeling for Galileo satellites , 2015, Journal of Geodesy.

[27]  S. N. Karutin,et al.  Optimization of the global network of tracking stations to provide GLONASS users with precision navigation and timing service , 2013 .

[28]  E. M. Standish.  The JPL Planetary and Lunar Ephemerides DE402/LE402 , 1995 .

[29]  Liao Ying.  The Effect of TT&C Deployment on the Regional Satellite Navigation System , 2007 .

[30]  Tianhe Xu,et al.  An Adaptive Kalman Filter Based on Sage Windowing Weights and Variance Components , 2003 .

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