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Imaging compensation of orbital motion for geostationary meteorological satellite

  • role： First author第一作者
  • Affiliation：

    Shanghai Institute of Satellite Engineering, Shanghai 201109, China

    General Technical Laboratory for Earth Remote Sensing Satellite, Shanghai 201109, China

  • Email：lvwang509@126.com
  • Introduction：吕旺，1983年生，男，高级工程师，研究方向为卫星图像导航与配准、卫星总体设计的理论和技术。E-mail：lvwang509@126.com
Wang LYU12,  
  • Affiliation：

    Shanghai Academy of Space Technology, Shanghai 201109, China

Yaohai DONG3,  
  • Affiliation：

    Shanghai Institute of Satellite Engineering, Shanghai 201109, China

Yili SHEN1,  
  • Affiliation：

    National Satellite Meteorological Center, Beijing 100081, China

Zhiqing ZHANG4,  
  • Affiliation：

    Shanghai Academy of Space Technology, Shanghai 201109, China

Wenqiang CHEN3

résumé

In recent years, a new generation of stationary meteorological satellites in various countries has adopted the three-axis stabilized mode of operation to scan the Earth for further improvement of observation frequency and signal–noise ratio. Image registration and navigation problems must be solved to accurately extract quantitative parameters of the Earth’s surface, clouds, and atmosphere at remote sensing target locations. Orbital drift movement is one of the main causes of satellite line-of-sight movement on the Earth’s surface. The relative movement generated between consecutive images affects the image registration accuracy of cloud animation. In this study, the imager on the Chinese FY-4 satellite that was launched in December 2016 is used as the research object. Moreover, a strict definition of image reference is given, and an orbital motion compensation method (OMC) is studied. By adding scan compensation to the imager 2-D scanning mechanism, the scanning path of the line of sight is navigated on the satellite in real time. Satellites are equivalent to viewing at ideal orbital positions. As a result, satellite remote sensing images are accurately registered to the Earth-fixed grid, and a relatively fixed geometric relationship is maintained. The correlation between L0 data and the measurement information of satellite orbit is removed due to the compensation performed on the satellite. Therefore, the long-term registration stability of the original image is guaranteed from the root. L0 remote sensing data from the FY-4 on-orbit test are used for experimental verification to prove the accuracy of the method. The results show that the relative movement of the north–south directions of the cloud animation is reduced from 973.0 μrad to 75.6 μrad (3σ) and that of the east–west direction is reduced from 205.8 μrad to 81.2 μrad (3σ). The interference of the orbital motion on the image navigation and registration is effectively reduced by the OMC on the satellite. In view of the development trend of the future imager of the geostationary meteorological satellite, the problem of the edge pixel error of the long aperture array detector caused by satellite orbital motion compensation is analyzed. Furthermore, a solution to reduce the edge error by maintaining the satellite near 0° inclination using an electric propulsion system is proposed.

mots-clés

geostationary meteorological satellite;Fengyun-4;FY-4;image registration;INR;orbital motion compensation;OMC

References

  1. 1.
    Bay H, Ess A, Tuytelaars T and Van Gool L. 2008. Speeded-up robust features (SURF). Computer Vision and Image Understanding, 110(3): 346–359
  2. 2.
    Carlomusto M. 2017. Product definition and users’ guide (PUG) volume 5: level 2+ products for geostationary operational environmental satellite R series (GOES-R) core ground segment. CDRL SE-16. Melbourne, Florida: Harris Corporation Government Communications Systems
  3. 3.
    Carr J L. 2009. Twenty-five years of INR. The Journal of the Astro- nautical Sciences, 57(1/2): 505–515
  4. 4.
    Dong Y H. 2016. FY-4 meteorological satellite and its application prospect. Aerospace Shanghai, 33(2): 1–8 (
  5. 5.
    EUMETSAT. 2013. Coordination Group for Meteorological Satellites LRIT/HRIT Global Specification. CGMS/DOC/12/0017. Darmstadt: CGMS
  6. 6.
    Griffith P C. 2006. ABI delivers significantly increased capabilities over current imagers//Proceedings of the 4th GOES Users’ Conference. Broomfield, Colorado: [s.n.]
  7. 7.
    Hogan D, Werbos A, Bentley J, Kennelly E, Puhl-Quinn P, Tully G, Steinfelt E, Zaccheo T S and Davis W. 2014. Multi-mission remote sensing ground processing algorithms//Proceedings of the 94th AMS Annual Meeting. Atlanta, GA: [s.n.]
  8. 8.
    Kamel A A, Graul D W, Chan F N T and Gamble D W. 1987. Spacecraft camera image registration. U.S., No. 4, 688, 091
  9. 9.
    Kamel A A, Kim H, Yang D, Park C and Woo J. 2018. Generalized image navigation and registration method based on Kalman filter//Advances in Aerospace Guidance, Navigation and Control. Cham: Springer: 609–630
  10. 10.
    Krimchansky A. 2014. GOES-R Series Concept of Operations (CONOPS). 410-R-CONOPS-0008. NOAA
  11. 11.
    Lu F, Zhang X H, Chen B Y, Liu H, Wu R H, Han Q, Feng X H, Li Y and Zhang Z Q. 2017. FY-4 geostationary meteorological satellite imaging characteristics and its application prospects. Journal of Marine Meteorology, 37(2): 1–12 (
  12. 12.
    Lu F, Zhang X H and Xu J M. 2008. Image navigation for the FY2 geosynchronous meteorological satellite. Journal of Atmospheric and Oceanic Technology, 25(7): 1149–1165
  13. 13.
    Lu N M and Gu S Y. 2016. Review and prospect on the development of meteorological satellites. Journal of Remote Sensing, 20(5): 832–841 (
  14. 14.
    Lyu W, Dai S L, Dong Y H, Shen Y L, Song X Z and Wang T S. 2017a. Attitude motion compensation for imager on Fengyun-4 geostationary meteorological satellite. Acta Astronautica, 138: 290–294
  15. 15.
    Lyu W, Wang T S, Dong Y H and Shen Y L. 2017b. Imaging navigation and registration for geostationary imager. IEEE Geoscience and Remote Sensing Letters, 14(12): 2175–2179
  16. 16.
    Schmit T J, Griffith P, Gunshor M M, Daniels J M, Goodman S J and Lebair W J. 2017. A closer look at the ABI on the GOES-R series. Bulletin of the American Meteorological Society, 98(4): 681–698
  17. 17.
    Shang J, Liu C B, Yang L, Zhang Z Q and Wang J. 2017. Misalignment angle calculation accuracy analysis of three-axis stabilized geostationary satellite. Journal of Geoscience and Environment Protection, 5(12): 153–165
  18. 18.
    Shen Y L, Lv W, Yu Y J and Cheng W Q. 2014. Research of imager scan mirror’s thermal distortion model for image navigation and registration. Aerospace Shanghai, 31(2): 26–29, 72 (
  19. 19.
    Tang F, Dong H J, Li N and Liu C H. 2016. Geolocation errors and correction of FY-3B microwave radiation imager measurements. Journal of Remote Sensing, 20(6): 1342–1351 (
  20. 20.
    Tang S H, Qiu H and Ma G. 2016. Review on progress of the Fengyun meteorological satellite. Journal of Remote Sensing, 20(5): 842–849 (
  21. 21.
    Tehranian S, Carr J L, Yang S, Madani H, Vasanth S, McKenzie K, Schmit T J, Swaroop A and DiRosario R. 2008. Remapping GOES imager instrument data for South American operations, implementing the XGOHI system//Proceedings of the 5th GOES User’s Conference. New Orleans: [s.n.]
  22. 22.
    Virgilio V N. 2015. Geolocation of remotely sensed pixels by introspective landmarking. U.S., No. 8, 942, 421 B1
  23. 23.
    Xu J M, Yang J, Zhang Z Q and Sun A L. 2010. Chinese meteorological satellitas, achievements and applications. Meteorological Monthly, 36(7): 94–100 (
  24. 24.
    Yang J, Zhang Z Q, Wei C Y, Lu F and Guo Q. 2017. Introducing the new generation of Chinese geostationary weather satellites, Fengyun-4. Bulletin of the American Meteorological Society, 98(8): 1637–1658
  25. 25.
    Zhang R W. 1998. Satellite Orbit Attitude Dynamics and Control. Beijing: Beihang University Press: 7–17
  26. 26.
    Zhang Z Q, Dong Y H, Ding L, Wang G Q, Fang X, Zhang X X and Huang F X. 2016. China’s first second-generation FY-4 meteorological satellite launched. Aerospace China, (12): 6–12
  27. 27.
    Zhang Z Q, Lu F, Fang X, Tang S H, Zhang X H, Xu Y L, Han W, Nie S P, Shen Y B and Zhou Y Q. 2017. Application and development of FY-4 meteorological satellite. Aerospace Shanghai, 34(4): 8–19 (

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