предыдущий|следующий

Analysis and mitigation of the Center-of-Mass errors for InSAR baseline determination

  • role： First author第一作者
  • Affiliation：

    College of Science, National University of Defense Technology, Changsha 410073, China

  • Email：jucice@126.com
  • Introduction：鞠冰(1986—　)，男，博士研究生，研究方向为卫星精密轨道确定及应用。E-mail：jucice@126.com
JU Bing,  
  • Affiliation：

    College of Science, National University of Defense Technology, Changsha 410073, China

CHANG Xiao,  
  • Affiliation：

    College of Science, National University of Defense Technology, Changsha 410073, China

GU Defeng,  
  • Affiliation：

    College of Science, National University of Defense Technology, Changsha 410073, China

DUAN Xiaojun,  
  • Affiliation：

    College of Science, National University of Defense Technology, Changsha 410073, China

ZHU Jubo,  
  • Affiliation：

    College of Science, National University of Defense Technology, Changsha 410073, China

WANG Zhengming

реферат

High-precision inter-satellite baseline determination is essential for the distributed InSAR system. The reduced dynamic orbit determination method, which employs onboard GNSS measurements and the dynamical constraints, is most extensively used to generate a baseline solution between two formation-fly satellites in low-Earth orbits. However, the reference point of the dynamical model is the center-of-mass (CoM) of the satellite rather than the phase center of the SAR antenna. Owing to the effect of structural deformation and the inevitable formation-keeping maneuvers, the CoM of a satellite in orbit is usually different from the point calibrated on ground. Thus, the effect of CoM errors must be carefully considered in GNSS-based precision baseline determination; otherwise, CoM errors are likely to induce systematic errors in the spatial baseline solution of the InSAR formation. Simulations are carried out in this study to analyze and mitigate the effect of CoM errors on the InSAR baseline determination. First, a constant CoM error of 1 cm is added to the x-, y-, and z-directions of the satellite-fixed frame. Simulation results show that the effect of such 1 cm error in the x- and y-directions are extremely tiny and can be safely neglected. By contrast, the effect of CoM error in the z-direction is significant, and the results in a systematic variation in the baseline product. In view of this, we further propose two independent methods in GNSS-based InSAR baseline determination to mitigate the z-component CoM errors by adding the following: (1) constant empirical acceleration in the radial direction; (2) an offset parameter in the z-direction of the satellite-fixed frame. The first method is based on dynamical modeling and does not need any extra correction for CoM variations. In addition, the first method is suitable for the mitigation of the CoM errors caused by formation-keeping maneuvers. The second method is based on geometric modeling, and an online calibration for the CoM errors is necessary. Moreover, the second method is suitable for the CoM calibration at the beginning of the in-orbit validation phase. Both methods are proven effective according to the numerical experiments. The 3D RMS caused by the simulated 1 cm CoM errors in the satellite-fixed z-direction can be reduced from 8.8 mm to 0.13 mm and 0.09 mm, respectively. Over 98% of the CoM errors can be mitigated. Using our proposed methods, the systematic errors caused by the CoM offset in the baseline solution can be considerably mitigated. Compared with traditional in-orbit CoM calibration, the proposed method not only avoids the complex design for satellite attitude control but also improves the efficiency of the InSAR system. The current research is based on simulations. Further validation of real data will be carried out in future studies.

ключеви́че слова́

Center-of-Mass errors;distributed InSAR;inter-satellite baseline determination;spaceborne GNSS;empirical acceleration

References

  1. 1.
    Allende-Alba G and Montenbruck O. 2016. Robust and precise baseline determination of distributed spacecraft in LEO. Advances in Space Research, 57(1): 46–63
  2. 2.
    Antony J W, Gonzalez J H, Schwerdt M, Bachmann M, Krieger G and Zink M. 2013. Results of the TanDEM-X baseline calibration. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(3): 1495–1501
  3. 3.
    Bergman E V, Walker B K and Levy D R. 1987. Mass property estimation for control of asymmetrical satellites. Journal of Guidance, Control, and Dynamics, 10(5): 483–491
  4. 4.
    Beutler G, Jäggi A, Hugentobler U and Mervart L. 2006. Efficient satellite orbit modelling using pseudo-stochastic parameters. Journal of Geodesy, 80(7): 353–372
  5. 5.
    Gonzalez J H, Bachmann M, Krieger G and Fiedler H. 2010. Development of the TanDEM-X calibration concept: analysis of systematic errors. IEEE Transactions on Geoscience and Remote Sensing, 48(2): 716–726
  6. 6.
    Gu D F, Lai Y W, Liu J H, Ju B and Tu J. 2016. Spaceborne GPS receiver antenna phase center offset and variation estimation for the Shiyan 3 satellite. Chinese Journal of Aeronautics, 29(5): 1335–1344
  7. 7.
    Jäggi A, Montenbruck O, Moon Y, Wermuth M, König R, Michalak G, Bock H and Bodenmann D. 2012. Inter-agency comparison of TanDEM-X baseline solutions. Advances in Space Research, 50(2): 260–271
  8. 8.
    Ju B, Gu D F, Herring T A, Allende-Alba G, Montenbruck O and Wang Z M. 2017. Precise orbit and baseline determination for maneuvering low earth orbiters. GPS Solutions, 21(1): 53–64
  9. 9.
    Krieger G, Fiedler H, Hajnsek I, Eineder M, Werner M and Moreira A. 2005. TanDEM-X: mission concept and performance analysis//Proceedings of 2005 IEEE International Geoscience and Remote Sensing Symposium. Seoul, Korea: IEEE: 4890–4893 [DOI: 10.1109/IGARSS.2005.1526770]
  10. 10.
    Krieger G, Moreira A, Fiedler H, Hajnsek I, Werner M, Younis M and Zink M. 2007. TanDEM-X: A Satellite Formation for High-Resolution SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 45(11): 3317–3341
  11. 11.
    Krieger G, Zink M, Bachmann M, Bräutigam B, Schulze D, Martone M, Rizzoli P, Steinbrecher U, Walter Antony J, De Zan F, Hajnsek I, Papathanassiou K, Kugler F, Rodriguez Cassola M, Younis M, Baumgartner S, López-Dekker P, Prats P and Moreira A. 2013. TanDEM-X: a radar interferometer with two formation-flying satellites. Acta Astronautica, 89: 83–98
  12. 12.
    Kroes R, Montenbruck O, Bertiger W and Visser P. 2005. Precise GRACE baseline determination using GPS. GPS Solutions, 9(1): 21–31
  13. 13.
    Liu J H, Gu D F, Ju B, Lai Y W and Yi D Y. 2015. Relative clock estimation method between two LEO satellites with a double-difference solution constraint. Acta Astronautica, 109: 34–41
  14. 14.
    Liu J H, Gu D F, Ju B, Yao J, Duan X J and Yi D Y. 2014. Basic performance of BeiDou-2 navigation satellite system used in LEO satellites precise orbit determination. Chinese Journal of Aeronautics, 27(5): 1251–1258
  15. 15.
    Montenbruck O, Wermuth M and Kahle R. 2011. GPS based relative navigation for the TanDEM-X mission-first flight results. Navigation, 58(4): 293–304
  16. 16.
    Moon Y, Koenig R and Wermuth M. 2012. Operational precise baseline determination for TanDEM-X DEM processing//Proceedings of IEEE International Geoscience and Remote Sensing Symposium. Munich: IEEE: 1633–1636 [DOI: 10.1109/IGARSS.2012.6351215]
  17. 17.
    Richfield R F, Walker B K and Bergmann E V. 1988. Input selection for a second-order mass property estimator. Journal of Guidance, Control, and Dynamics, 11(3): 207–212
  18. 18.
    Tanygin S and Williams T. 1997. Mass property estimation using coasting maneuvers. Journal of Guidance, Control, and Dynamics, 20(4): 625–632
  19. 19.
    Tu J, Gu D F, Wu Y and Yi D Y. 2012. Error modeling and analysis for InSAR spatial baseline determination of satellite formation flying. Mathematical Problems in Engineering, 2012: Article ID 140301 [DOI: 10.1155/2012/140301]
  20. 20.
    Wang B L, Liao H and Han Y. 2010. On-Orbit calibration of satellite center of mass based on MME/EKF algorithm. Journal of Astronautics, 31(9): 2150–2156
  21. 21.
    Wang B N and Xiang M S. 2009. Relative height accuracy analysis of TanDEM-X system. Journal of Remote Sensing, 13(1): 49–53
  22. 22.
    Wang F R, Bettadpur S V, Save H and Kruizinga G. 2010. Determination of Center-of-Mass of gravity recovery and climate experiment satellites. Journal of Spacecraft and Rockets, 47(2): 371–379
  23. 23.
    Wang Q S, Qu J S, Huang H F, Yu A X and Dong Z. 2012. A method based on integrating real and complex correlation function for InSAR image coregistration. Acta Geodaetica et Cartographica Sinica, 41(4): 563–569
  24. 24.
    Wermuth M, Montenbruck O and Wendleder A. 2011. Relative navigation for the TanDEM-X mission and evaluation with DEM calibration results. Journal of Aerospace Engineering, Sciences and Applications, 3(2): 28–38
  25. 25.
    Wu S C, Yunck T P and Thornton C L. 1991. Reduced-dynamic technique for precise orbit determination of low earth satellites. Journal of Guidance, Control, and Dynamics, 14(1): 24–30

Читать полностью

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website