Journal of Radio Electronics. eISSN 1684-1719. 2024. 1
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DOI: https://doi.org/10.30898/1684-1719.2024.1.4

 

impact OF the EVAPORATION DUCT UNCERTAINTY
ON the TROPOSPHERIC RADIO WAVE PROPAGATION

 

M.S. Lytaev

 

St. Petersburg Federal Research Center of the Russian Academy of Sciences
199178, Russia, Saint Petersburg, 14 Linia, 39

 

The paper was received October 17, 2023.

 

Abstract. This study is dedicated to the radio wave propagation modeling in the evaporation duct. Special attention is given to the fact that the parameters of tropospheric waveguides are practically always determined with some degree of error. An algorithm based on the parabolic equation method has been developed, which takes into account the measurement error of the tropospheric refractive index and assesses the statistical characteristics of the spatial distribution of radio wave amplitude. A series of numerical experiments have been conducted for various propagation conditions. It has been demonstrated that in many cases, ignoring the refractive index error can lead to significant discrepancies in simulation results.

Key words: stochastic parabolic equation, tropospheric waveguide, Monte Carlo method.

Financing: This study was supported by the Russian Science Foundation grant №23-71-00069.

Corresponding author: Lytaev Mikhail Sergeevich, mlytaev@yandex.ru

References

1. Zhang J.P. et al. A four-parameter M-profile model for the evaporation duct estimation from radar clutter //Progress In Electromagnetics Research. – 2011. – Т. 114. – С. 353-368.

2. Ivanov V.K., Shalyapin V.N., Levadnyi Y.V. Determination of the evaporation duct height from standard meteorological data //Izvestiya, atmospheric and oceanic physics. – 2007. – Т. 43. – №. 1. – С. 36-44.

3. Ji H. et al. Joint inversion of evaporation duct based on radar sea clutter and target echo using deep learning //Electronics. – 2022. – Т. 11. – №. 14. – С. 2157.

4. Karimian A. et al. Refractivity estimation from sea clutter: An invited review //Radio science. – 2011. – Т. 46. – №. 06. – С. 1-16.

5. Huang L.F. et al. Comparative analysis of intelligent optimization algorithms for atmospheric duct inversion using Automatic Identification System signals //Remote Sensing. – 2023. – Т. 15. – №. 14. – С. 3577.

6. Михайлов М.С. и др. Влияние тропосферных волноводов на работу радиолокатора над морской поверхностью [The influence of troposperic ducts on the radar operation above the sea surface] //Радиолокация, навигация, связь. – 2018. – С. 23-34.

7. Zhang H. et al. Statistical modeling of evaporation duct channel for maritime broadband communications //IEEE Transactions on Vehicular Technology. – 2022. – Т. 71. – №. 10. – С. 10228-10240.

8. Пищин О.Н., Пузанков Д.С., Лыдкина К.С. Методика расчета влияния фактора сезонности на распространение радиоволн в южных регионах России вблизи гидросферных объектов в диапазоне ультравысоких частот [Methods of calculating influence of seasonality factor on propagation of radio waves in southern regions of Russia close to hydrospheric objects in ultra-high frequency range] //Вестник Астраханского государственного технического университета. Серия: Управление, вычислительная техника и информатика. – 2022. – №. 3. – С. 51-60.

9. Fock V.A. Electromagnetic diffraction and propagation problems. – Pergamon press, 1965.

10. Ахияров В.В. Вычисление множителя ослабления над земной поверхностью методом параболического уравнения [Path loss prediction over irregular terrains based on parabolic equation] //Журнал радиоэлектроники. – 2012. – №. 1.

11. Levy M. Parabolic equation methods for electromagnetic wave propagation. – IET, 2000. – №. 45.

12. Lytaev M.S. Reducing the numerical dispersion of the one-way Helmholtz equation via the differential evolution method //Journal of Computational Science. – 2023. – Т. 71. – С. 102057.

13. Илюшин Я.А. и др. Решение параболического уравнения дифракции при радиопросвечивании ионосферных слоев [Solution of parabolic diffraction equation for the case of occultation of layered structures in the ionosphere] //Журнал радиоэлектроники. – 2013. – №. 11.

14. Enstedt M., Wellander N. A spectral expansion-based Fourier split-step method for uncertainty quantification of the propagation factor in a stochastic environment //Radio science. – 2016. – Т. 51. – №. 11. – С. 1783-1791.

15. Ахияров В.В. Моделирование дальнего тропосферного распространения радиоволн методом параболического уравнения [Modeling of tropospheric radio wave propagation by the parabolic equation method] //Журнал радиоэлектроники. – 2022. – №. 1.

16. Oksendal B. Stochastic differential equations: an introduction with applications. – Springer Science & Business Media, 2013.

17. Lytaev M.S. Rational interpolation of the one-way Helmholtz propagator //Journal of Computational Science. – 2022. – Т. 58. – С. 101536.

18. Fishman L., McCoy J. J. Derivation and application of extended parabolic wave theories. I. The factorized Helmholtz equation //Journal of Mathematical Physics. – 1984. – Т. 25. – №. 2. – С. 285-296.

19. Лытаев М.С. О применении конечно-разностной аппроксимации Паде псевдодифференциального параболического уравнения в задаче тропосферного распространения радиоволн [On application of the finite-difference Padé approximation of the pseudo-differential parabolic equation to the tropospheric radio wave propagation problem] //Вычислительные методы и программирование. – 2020. – Т. 21. – №. 4. – С. 405-419.

20. Ozgun O. et al. PETOOL v2. 0: Parabolic Equation Toolbox with evaporation duct models and real environment data //Computer physics communications. – 2020. – Т. 256. – С. 107454.

21. Brookner E., Cornely P.R., Lok Y.F. AREPS and TEMPER-getting familiar with these powerful propagation software tools //2007 IEEE Radar Conference. – IEEE, 2007. – С. 1034-1043.

22. Zhou H., Chabory A., Douvenot R. A fast wavelet-to-wavelet propagation method for the simulation of long-range propagation in low troposphere //IEEE Transactions on Antennas and Propagation. – 2021. – Т. 70. – №. 3. – С. 2137-2148.

23. Lytaev M.S. Fresnel reflection modeling within the higher-order parabolic equation and discrete nonlocal boundary conditions //2022 IEEE Radar Conference (RadarConf22). – IEEE, 2022. – С. 1-5.

24. Lytaev M.S. Nonlocal boundary conditions for split-step padé approximations of the helmholtz equation with modified refractive index //IEEE antennas and wireless propagation letters. – 2018. – Т. 17. – №. 8. – С. 1561-1565.

25. Лытаев М.С. Численный метод расчета тропосферного распространения электромагнитных волн в задачах построения геоинформационных систем дистанционного мониторинга [A Numerical Method for Estimating Tropospheric Radio Wave Propagation for Remote Monitoring Geoinformation Systems] //Труды СПИИРАН. – 2018. – Т. 1. – №. 56. – С. 195-213.

26. Кузнецов Д.Ф. Стохастические дифференциальные уравнения: теория и практика численного решения [Stochastic differential equations: theory and practice of numerical solution]. Спб: Изд-во Политехн. Ун-та – 2009.

27. Higham D.J. An algorithmic introduction to numerical simulation of stochastic differential equations //SIAM review. – 2001. – Т. 43. – №. 3. – С. 525-546.

28. PyWaveProp. URL: https://github.com/mikelytaev/wave-propagation (дата обращения: 05.10.2023).

For citation:

Lytaev M.S. Impact of the evaporation duct uncertainty on the tropospheric radio wave propagation. // Journal of Radio Electronics. – 2024. – №. 1. https://doi.org/10.30898/1684-1719.2024.1.4 (In Russian)