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Atmospheric and Oceanic Optics

, Volume 29, Issue 6, pp 533–540 | Cite as

Three algorithms of statistical modeling in problems of optical communication on scattered radiation and bistatic sensing

  • V. V. BelovEmail author
  • M. V. Tarasenkov
Remote Sensing of Atmosphere, Hydrosphere, and Underlying Surface

Abstract

Three algorithms of the Monte Carlo method for the calculation of the pulse reaction in channels of laser sensing and communication are considered: the local estimation algorithm, double local estimation algorithm, and proposed modified double local estimation algorithm. Results of testing the algorithms and their comparison are shown. For the case of a homogeneous medium, the performances of the algorithms are compared. The comparison shows conditions for which the proposed algorithm has the advantage over the double local estimation algorithm. The contribution of double, triple, and higher multiplicity scattering is estimated. The high contribution of multiple scattering justifies the applicability of the Monte Carlo method for solving such problems.

Keywords

Monte Carlo method multiple scattering optical communication bistatic sensing pulse reaction 

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References

  1. 1.
    J. A. Reagan, D. M. Byrne, M. D. King, J. D. Spinhirne, and B. M. Herman, “Determination of the somplex refractive-index and size distribution of atmospheric particulates from bistatic-monostatic lidar and solar radiometer measurements,” J. Geophys. Res. Oceans 85 (C3), 1591–1599 (1980).ADSCrossRefGoogle Scholar
  2. 2.
    K. Meki, K. Yamaguchi, X. Li, Y. Saito, T. D. Kawahara, and A. Nomura, “Range-resolved bistatic imaging lidar for the measurement of the lower atmosphere,” Opt. Lett. 21 (17), 1318–1320 (1996).ADSCrossRefGoogle Scholar
  3. 3.
    N. Sugimoto, “Two-color dual-polarization pulsed bistatic lidar for measuring water cloud droplet size,” Opt. Rev. 7 (3), 235–240 (2000).CrossRefGoogle Scholar
  4. 4.
    J. E. Barnes, N. C. P. Sharma, and T. B. Kaplan, “Atmospheric aerosol profiling with a bistatic imaging lidar system,” Appl. Opt. 46 (15), 2922–2929 (2007).ADSCrossRefGoogle Scholar
  5. 5.
    K. F. G. Olofson, G. Witt, and J. B. C. Peterson, “Bistatic lidar mesurements of clouds in the Nordic Arctic region,” Appl. Opt. 47 (26), 4777–4786 (2008).ADSCrossRefGoogle Scholar
  6. 6.
    E. G. Kablukova and B. A. Kargin, “Efficient discrete stochastic modification for local estimates of the Monte Carlo method for problems of laser sounding of scattering media,” Vychislit. Tekhnol. 17 (3), 70–82 (2012).Google Scholar
  7. 7.
    E. G. Kablukova, B. A. Kargin, A. A. Lisenko, G. G. Matvienko, and E. N. Chesnokov, “Numerical statistical simulation of terahertz radiation propagation in cloudiness,” Opt. Atmos. Okeana 27 (11), 939–948 (2014).Google Scholar
  8. 8.
    E. G. Kablukova, B. A. Kargin, A. A. Lisenko, and G. G. Matvienko, “Numerical simulation of polarization characteristics of an echo signal in the process of ground-based cloud sensing in the terahertz range,” Atmos. Ocean. Opt. 29 (1), 33–41 (2016).CrossRefGoogle Scholar
  9. 9.
    G. M. Krekov, “Technique for the local estimation of fluxes in broadband lidar sensing problems,” Atmos. Ocean. Opt. 23 (2), 152–160 (2010).CrossRefGoogle Scholar
  10. 10.
    G. M. Krekov, M. M. Krekova, and A. Ya. Sukhanov, “Estimate of perspective white-light lidar efficiency for sensing of the stratus clouds microphysical parameters: 2. Parametric modification of the iteration method lidar equation solution,” Opt. Atmos. Okeana 22 (8), 795–802 (2009).Google Scholar
  11. 11.
    H. Yin, S. Chang, H. Jia, Ji. Yang, and Ju. Yang, “Nonline-of-sight multiscatter propagation model,” J. Opt. Soc. Amer. 26 (11), 2466–2469 (2009).ADSCrossRefGoogle Scholar
  12. 12.
    H. Ding, G. Chen, A. K. Majumdar, B. M. Sadler, and Z. Xu, “Modeling of non-line-of-sight ultraviolet scattering channels for communication,” IEEE J. Selec. Areas. Commun. 27 (9), 1535–1544 (2009).CrossRefGoogle Scholar
  13. 13.
    H. Yin, H. Jia, H. Zhang, X. Wang, S. Chang, and J. Yang, “Vectorized polarization-sensitive model of non-line-of-sight multiple-scatter propagation,” J. Opt. Soc. Amer., A 28 (10), 2082–2085 (2011).ADSCrossRefGoogle Scholar
  14. 14.
    D. Han, X. Fan, K. Zhang, and R. Zhu, “Research on multiple-scattering channel with Monte Carlo model in UV atmosphere communication,” Appl. Opt. 52 (22), 5516–5522 (2013).ADSCrossRefGoogle Scholar
  15. 15.
    H. Xiao, Y. Zuo, J. Wu, Y. Li, and J. Lin, “Non-lineof-sight ultraviolet single-scatter propagation model in random turbulent medium,” Opt. Lett. 38 (17), 3366–3369 (2013).ADSCrossRefGoogle Scholar
  16. 16.
    V. V. Belov, M. V. Tarasenkov, V. N. Abramochkin, V. V. Ivanov, A. V. Fedosov, V. O. Troitskii, and D. V. Shiyanov, “Atmospheric bistatic communication channels with scattering. Part 1. Methods of study,” Atmos. Ocean. Opt. 26 (5), 364–370 (2013).CrossRefGoogle Scholar
  17. 17.
    H. Yin, S. Chang, X. Wang, Ji. Yang, Ju. Yang, and J. Tan, “Analytical model of non-line-of-sight singlescatter propagation,” J. Opt. Soc. Amer., A 27 (7), 1505–1509 (2010).ADSCrossRefGoogle Scholar
  18. 18.
    M. A. Elshimy and S. Hranilovic, “Non-line-of-sight single-scatter propagation model for noncoplanar geometries,” J. Opt. Soc. Amer., A 28 (3), 420–428 (2011).ADSCrossRefGoogle Scholar
  19. 19.
    G. Z. Lotova, “Modification of the double local estimate of the Monte-Carlo method in radiation transfer theory,” Rus. J. Numer. Anal. Math. Model. 26 (5), 491–500 (2011).MathSciNetzbMATHGoogle Scholar
  20. 20.
    G. A. Mikhailov and G. Z. Lotova, “A numerical-statistical estimate for a particle flux with finite variance,” Dokl. Math. 86 (3), 743–746 (2012).MathSciNetCrossRefzbMATHGoogle Scholar
  21. 21.
    G. I. Marchuk, G. A. Mikhailov, M. A. Nazaraliev, R. A. Darbinyan, B. A. Kargin, and B. S. Elepov, Monte Carlo Method in Atmospheric Optics (Nauka, Novosibirsk, 1976) [in Russian].Google Scholar
  22. 22.
    T. A. Sushkevich, Mathematical Models of Radiation Transfer (BINOM, Laboratoriya znanii, Moscow, 2005) [in Russian].zbMATHGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2016

Authors and Affiliations

  1. 1.V.E. Zuev Institute of Atmospheric Optics, Siberian BranchRussian Academy of SciencesTomskRussia
  2. 2.Tomsk State UniversityTomskRussia

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