The challenge of precise orbit determination for STSAT-2C using extremely sparse SLR data

Abstract The Science and Technology Satellite (STSAT)-2C is the first Korean satellite equipped with a laser retro-reflector array for satellite laser ranging (SLR). SLR is the only on-board tracking source for precise orbit determination (POD) of STSAT-2C. However, POD for the STSAT-2C is a challenging issue, as the laser measurements of the satellite are extremely sparse, largely due to the inaccurate two-line element (TLE)-based orbit predictions used by the SLR tracking stations. In this study, POD for the STSAT-2C using extremely sparse SLR data is successfully implemented, and new laser-based orbit predictions are obtained. The NASA/GSFC GEODYN II software and seven-day arcs are used for the SLR data processing of two years of normal points from March 2013 to May 2015. To compensate for the extremely sparse laser tracking, the number of estimation parameters are minimized, and only the atmospheric drag coefficients are estimated with various intervals. The POD results show that the weighted root mean square (RMS) post-fit residuals are less than 10 m, and the 3D day boundaries vary from 30 m to 3 km. The average four-day orbit overlaps are less than 20/330/20 m for the radial/along-track/cross-track components. The quality of the new laser-based prediction is verified by SLR observations, and the SLR residuals show better results than those of previous TLE-based predictions. This study demonstrates that POD for the STSAT-2C can be successfully achieved against extreme sparseness of SLR data, and the results can deliver more accurate predictions.

[1]  Kyu-Hong Choi,et al.  Satellite orbit determination using a batch filter based on the unscented transformation , 2010 .

[2]  E. Park,et al.  Orbit determination and analysis for STSAT-2C , 2013 .

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

[4]  Paweł Lejba,et al.  Determination of orbits and SLR stations’ coordinates on the basis of laser observations of the satellites Starlette and Stella , 2007 .

[5]  Y. Kwak,et al.  Mass density of the upper atmosphere derived from Starlette’s Precise Orbit Determination with Satellite Laser Ranging , 2011 .

[6]  M. Cheng,et al.  GGM02 – An improved Earth gravity field model from GRACE , 2005 .

[7]  Pascal Willis,et al.  Refining DORIS atmospheric drag estimation in preparation of ITRF2008 , 2010 .

[8]  Michael R Pearlman,et al.  THE INTERNATIONAL LASER RANGING SERVICE , 2007 .

[9]  Richard D. Ray,et al.  A Global Ocean Tide Model From TOPEX/POSEIDON Altimetry: GOT99.2 , 1999 .

[10]  H. Bock,et al.  GOCE orbit predictions for SLR tracking , 2011 .

[11]  D. Kucharski,et al.  Orbit Determination Using SLR Data for STSAT-2C: Short-arc Analysis , 2015 .

[12]  Marcin Jagoda,et al.  Estimation of the Love and Shida numbers: h2, l2 using SLR data for the low satellites ☆ , 2013 .

[13]  E. Park A Status Report on KASI Prediction Center (KAS) , 2014 .

[14]  Chandeok Park,et al.  Precise orbit determination using the batch filter based on particle filtering with genetic resampling approach , 2014 .

[15]  Paweł Lejba,et al.  Determination of station positions and velocities from laser ranging observations to Ajisai, Starlette and Stella satellites , 2011 .

[16]  E. C. Pavlis,et al.  High‐accuracy zenith delay prediction at optical wavelengths , 2004 .

[17]  Z. Altamimi,et al.  ITRF2005 : A new release of the International Terrestrial Reference Frame based on time series of station positions and Earth Orientation Parameters , 2007 .

[18]  R. Langley,et al.  Improved mapping functions for atmospheric refraction correction in SLR , 2002 .

[19]  Jong-Uk Park,et al.  Analysis of Scaling Parameters of the Batch Unscented Transformation for Precision Orbit Determination using Satellite Laser Ranging Data , 2011 .

[20]  Thomas A. Herring,et al.  Modeling of nutation and precession: New nutation series for nonrigid Earth and insights into the Ea , 2002 .

[21]  Georg Kirchner,et al.  Space debris orbit prediction errors using bi-static laser observations. Case study: ENVISAT , 2015 .

[22]  A. Hedin Extension of the MSIS Thermosphere Model into the middle and lower atmosphere , 1991 .

[23]  Z. Altamimi,et al.  ITRF2008: an improved solution of the international terrestrial reference frame , 2011 .

[24]  Yoaz Bar-Sever,et al.  Effects of thermosphere total density perturbations on LEO orbits during severe geomagnetic conditions (Oct–Nov 2003) using DORIS and SLR data , 2005 .