Diffractive Integrals for Bistatic Remote Sensing Using GPS Signals

  • Alexander Pavelyev
  • Jens Wickert
  • Yuei-An Liou


Diffractive integrals use a reference signal to derive the field distribution from the radio holograms. The phase of reference signal coincides with phase of the Green function and can be found by solving the scalar wave equation. This property of the reference signal demonstrates a fundamental nature of the radio holographic focused synthetic aperture principle (RFSA) specifically in its application to the radio occultation (RO) data analysis. The RFSA method has been validated by direct observations of multi-beam propagation in the atmosphere and weak reflections from the terrestrial surface, its vertical resolution has been estimated early as about 70 m. To compare the Canonical Transform (CT), Back Propagation (BP) and RFSA methods a general inverse operator (GIO) is introduced. CT as a partial case of GIO method can resolve physical rays in multi-path situations under an assumption of the global spherical symmetry of the atmosphere and ionosphere. RFSA method can account for the multi-path in the case when the global spherical symmetry is absent by using the appropriate model of the refractivity and has a promise to be effective for operational data analysis.

Key words

diffractive integrals bistatic remote sensing radio occultation 


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  1. 1.
    Zverev VA (1975) Radio-optics. Soviet Radio, Moscow.Google Scholar
  2. 2.
    Marouf EA and Tyler GL (1982) Microwave edge diffraction by features in Saturn's rings: Observations with Voyager 1. Science 217: 243–245.Google Scholar
  3. 3.
    Gorbunov ME, Gurvich AS, Bengtsson L (1996) Advanced algorithms of inversion of GPS-MET satellite data and their application to reconstruction of temperature and humidity. Max-Planck-Inst Meteor, Rep 211, ISSN 0937-1060.Google Scholar
  4. 4.
    Hocke K, Pavelyev A, Yakovlev O, Barthes L and Jakowski N (1999) Radio occultation data analysis by radio holographic method. J Atmos Solar-Terr Phys 61: 1169–1177.CrossRefGoogle Scholar
  5. 5.
    Pavelyev AG (1998) On the possibility of radio holographic investigation on communication link satellite-to-satellite. J Comm Technology and Electronics 43(8): 126–131.Google Scholar
  6. 6.
    Igarashi K, Pavelyev A, Hocke K, Pavelyev D, and Wickert J (2001) Observation of wave structures in the upper atmosphere by means of radio holographic analysis of the RO data. Adv Space Res 27(6–7): 1321–1327.CrossRefGoogle Scholar
  7. 7.
    Pavelyev AG, Liou YA, Huang CY, Reigber C, Wickert J, Igarashi K, Hocke K (2002) Radio holographic method for the study of the ionosphere, atmosphere and terrestrial surface from space using GPS occultation signals. GPS Solutions (No. 6): 101–108.CrossRefGoogle Scholar
  8. 8.
    Beyerle G, Hocke K, Wickert J, Schmidt T, Marquardt C, and Reigber Ch (2002) GPS ROs with CHAMP: A radio holographic analysis of GPS signal propagation in the troposphere and surface reflections. J Geophys Res 107(D24): 10.1029/2001JD001402.Google Scholar
  9. 9.
    Gorbunov M E (2002) Canonical transform method for processing radio occultation data in the lower troposphere, Radio Sci 37(5): 10.1029/2000RS002592.Google Scholar
  10. 10.
    Jensen AS, Lohmann MS, Benzon HH and Nielsen A S (2003) Full spectrum inversion of radio occultation signal, Radio Sci 38(3): 10.1029/2002RS002763.Google Scholar
  11. 11.
    Yu V and Egorov (1985) Lectures on partial differential equations. Additional chapters, Moscow State University Press, Moscow (in Russian).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Alexander Pavelyev
    • 1
  • Jens Wickert
    • 2
  • Yuei-An Liou
    • 3
  1. 1.Institute of Radio Engineering and Electronics of Russian Academy of Sciences (IRE RAS) FryazinoMoscow regionRussia
  2. 2.Department Geodesy and Remote SensingGeoForschungsZentrum Potsdam (GFZ)PotsdamGermany
  3. 3.Center for Space and Remote Sensing ResearchNational Central UniversityJung-LiTaiwan

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