Retrieval of crosswind velocity based on the analysis of remote object images: Part 1 — drift of a thin layer of turbulent inhomogeneities


Numerical simulation is carried out in order to estimate possibilities of crosswind velocity determination along an observation path between a distant object and observer. The estimation is based on the analysis of atmospheric distortions in the object images. The disturbing effect of limited atmospheric regions on the object image and possibilities of the drift velocity retrieval in these regions are analyzed. A new method for filtration of turbulent distortions by their characteristic sizes is suggested with the aim of estimating the wind velocity at different segments of the observation path. It is shown that the technique suggested allows one to determine crosswind velocity with high accuracy when it is applied to a thin layer of atmospheric inhomogeneities.

This is a preview of subscription content, access via your institution.


  1. 1.

    V. A. Banakh, D. A. Marakasov, and M. A. Vorontsov, “Cross-wind profiling based on the scattered wave scintillations in a telescope focus,” Appl. Opt. 46 (33), 8104–8117 (2007).

    ADS  Article  Google Scholar 

  2. 2.

    V. A. Banakh and D. A. Marakasov, “Wind velocity profile reconstruction from intensity fluctuations of a plane wave propagating in a turbulent atmosphere,” Opt. Lett. 32 (15), 2236–2238 (2007).

    ADS  Article  Google Scholar 

  3. 3.

    V. A. Banakh and D. A. Marakasov, “Wind profiling based on the optical beam intensity statistics in a turbulent atmosphere,” J. Opt. Soc. Am., A 24 (10), 3245–3254 (2007).

    ADS  Article  Google Scholar 

  4. 4.

    D. A. Marakasov, “Algorithm for reconstruction of wind profile from turbulent intensity fluctuations of a scattered wave in a receiving telescope,” Atmos. Ocean. Opt. 20 (12), 1014–1018 (2007).

    Google Scholar 

  5. 5.

    L. V. Antoshkin, V. V. Lavrinov, L. N. Lavrinova, and V. P. Lukin, “Differential method for wavefront sensor measurements of turbulence parameters and wind velocity,” Atmos. Ocean. Opt. 21 (1), 64–68 (2008).

    Google Scholar 

  6. 6.

    D. A. Marakasov, D. S. Rychkov, and A. V. Falits, “Reconstruction of cross-wind and structure characteristic profiles from turbulent intensity fluctuations of laser beam,” Opt. Atmos. Okeana 22 (1), 82–85 (2009).

    Google Scholar 

  7. 7.

    D. A. Marakasov, “Wind profiling reconstruction from laser beam intensity fluctuations in a receiving telescope,” Opt. Atmos. Okeana 23 (4), 304–307 (2010).

    Google Scholar 

  8. 8.

    A. L. Afanas’ev, V. A. Banakh, and A. P. Rostov, “Estimate of wind velocity in the atmosphere based on an analysis of turbulent distortions of laser beam images registered by video camera,” Atmos. Ocean. Opt. 24 (1), 88–94 (2011).

    Article  Google Scholar 

  9. 9.

    R. B. Holmes, US Patent No. 5469250 O05469250 (21 November 1995).

    Google Scholar 

  10. 10.

    M. Belenkii, Pat. Appl. No. 2010/0128136 A1, US (May 27, 2010).

    Google Scholar 

  11. 11.

    V. V. Dudorov and A. S. Eremina, “Determination of atmospheric turbulent inhomogeneity wind drift from sequence of incoherent images,” Proc. SPIE 9292, 1–6 (2014).

    Google Scholar 

  12. 12.

    A. S. Eremina and V. V. Dudorov, “A method for turbulent distortions filtering and determining their shift speed from video of optical images in the case of atmospheric inhomogeneities by wind drift,” Izv. vuzov, Fiz. 58 (8/2), 192–194 (2015).

    Google Scholar 

  13. 13.

    V. V. Dudorov and A. S. Eremina, “Filtration of optical image distortions for retrieving the drift velocity of atmospheric turbulence inhomogeneities,” Proc. SPIE 9680, 1–8 (2015).

    Google Scholar 

  14. 14.

    A. L. Afanasiev, V. A. Banakh, and A. P. Rostov, “Estimation of the integral wind velocity and turbulence in the atmosphere from distortions of optical images of naturally illuminated objects,” Atmos. Ocean. Opt. 29 (5), 422–430 (2016).

    Article  Google Scholar 

  15. 15.

    D. A. Marakasov, “Estimation of mean wind velocity from correlations of centers of gravity shifings for noncoherent sources in the turbulent atmosphere,” Opt. Atmos. Okeana 29 (4), 294–299 (2016).

    Google Scholar 

  16. 16.

    V. V. Dudorov and A. S. Eremina, “Possibilities of crosswind profiling based on incoherent imaging,” Proc. SPIE 10035, 1–7 (2016).

    Google Scholar 

  17. 17.

    M. A. Vorontsov and V. V. Kolosov, “Target-in-theloop beam control: Basic considerations for analysis and wave-front sensing,” J. Opt. Soc. Am., A 22, 126–141 (2005).

    ADS  Article  Google Scholar 

  18. 18.

    V. V. Dudorov, M. A. Vorontsov, and V. V. Kolosov, “Speckle field propagation in “frozen” turbulence: Brightness function approach,” J. Opt. Soc. Am., A 23 (8), 1924–1936 (2006).

    ADS  Article  Google Scholar 

  19. 19.

    V. V. Dudorov, V. V. Kolosov, and G. A. Filimonov, “Algorithm for formation of infinite turbulent screens for simulation of long-term laser experiments in the atmosphere,” Izv. Tomsk. Politekhn. Un-ta 309 (8), 85–89 (2006).

    Google Scholar 

  20. 20.

    V. V. Dudorov, G. A. Filimonov, and V. V. Kolosov, “Algorithm for formation of an infinite random turbulent screen,” Proc. SPIE 6160, CID:61600R (2005).

    Google Scholar 

  21. 21.

    S. L. Lachinova, M. A. Vorontsov, V. V. Dudorov, V. V. Kolosov, and M. T. Valley, “Anisoplanatic imaging through atmospheric turbulence: Brightness function approach,” Proc. SPIE 6708, 67080E (2007).

    ADS  Article  Google Scholar 

  22. 22.

    V. V. Dudorov and V. V. Kolosov, “Anisoplanatic turbulence correction in incoherent imaging by using reference sources with different wavelengths,” Atmos. Ocean. Opt. 23 (5), 353–358 (2010).

    Article  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to V. V. Dudorov.

Additional information

Original Russian Text © V.V. Dudorov, A.S. Eremina, 2017, published in Optika Atmosfery i Okeana.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dudorov, V.V., Eremina, A.S. Retrieval of crosswind velocity based on the analysis of remote object images: Part 1 — drift of a thin layer of turbulent inhomogeneities. Atmos Ocean Opt 30, 422–428 (2017).

Download citation


  • wind
  • turbulent atmosphere
  • incoherent image