Journal of Radio Electronics. eISSN 1684-1719. 2025. ¹3
Full text in Russian (pdf)
DOI: https://doi.org/10.30898/1684-1719.2025.3.11
TROPOSpHERIC REFRACTION SENSING
USING THE AUTOMATIC DIFFERENTIATION
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 December 6, 2024.
Abstract. A method for indirect measuring the vertical profile of the tropospheric refractive index is proposed. The method is based on analyzing the distortion of a radio signal as it propagates near the Earth's surface from a known source to an array of receivers. The parabolic equation method is chosen as the direct model. Automatic differentiation with respect to the unknown parameters of the target profile is applied to the finite-difference numerical scheme. This approach enables efficient computation of the gradient required for solving the optimization problem. Computational experiments conducted for various profiles and frequencies demonstrate the adequacy and effectiveness of the proposed method.
Key words: inverse problem, tropospheric refractive index, parabolic equation, tropospheric waveguide.
Financing: This study was supported by the Russian Science Foundation grant ¹23-71-00069.
Corresponding author: Lytaev Mikhail Sergeevich, mlytaev@yandex.ru
References
1. Lytaev M.S. Impact of the evaporation duct uncertainty on the tropospheric radio wave propagation. // Journal of Radio Electronics. – 2024. – No. 1. (In Russian)
2. Wang S. et al. Long-term over-the-horizon microwave channel measurements and
statistical analysis in evaporation ducts over the yellow sea // Frontiers in Marine Science. – 2023. – Vol. 10.
3. Dinc E., Akan O. B. Channel model for the surface ducts: Large-scale path-loss, delay spread, and AOA // IEEE Transactions on Antennas and Propagation. – 2015. – Vol. 63. – No. 6. – pp. 2728-2738.
4. Levy M. Parabolic equation methods for electromagnetic wave propagation. – IET, 2000.
5. Wang Q. è äð. CASPER: Coupled air–sea processes and electromagnetic ducting research //Bulletin of the American Meteorological Society. – 2018. – Vol. 99. – No. 7. – pp. 1449-1471.
6. Wang S. et al. Observations of anomalous over-the-horizon propagation in the evaporation duct induced by Typhoon Kompasu (202118) //IEEE Antennas and Wireless Propagation Letters. – 2022. – Vol. 21. – No. 5. – pp. 963-967.
7. Tichonov A. N., Leonov A. S., Jagola A. G. Nonlinear ill-posed problems. – London: Chapman & Hall, 1998.
8. Tarantola A. Inverse problem theory and methods for model parameter estimation. – SIAM, 2005.
9. Zhao X., Huang S., Du H. Theoretical analysis and numerical experiments of variational adjoint approach for refractivity estimation //Radio Science. – 2011. – Vol. 46. – No. 01.
10. Pastore D. et al. Refractivity inversions from point-to-point X-band radar propagation measurements //Radio Science. – 2022. – Vol. 57. – No. 2.
11. Karabaş U., Diouane Y., Douvenot R. A variational adjoint approach on wide-angle parabolic equation for refractivity inversion //IEEE Transactions on Antennas and Propagation. – 2021. – Vol. 69. – No. 8. – pp. 4861-4870.
12. Karimian A. et al. Refractivity estimation from sea clutter: An invited review //Radio science. – 2011. – Vol. 46. – No. 06.
13. Bazarova A. S. et al. Daily Variations in Refraction Gradient within the Lowest 10-Meter Layer of the Troposphere //Vestnik of Volga Stat University of Technology. Ser.: Radio Engineering and Infocommunication Systems. – 2023. – Vol. 29. – No. 3. – pp. 21-32. (In Russian)
14. Akhiyarov V. V. Path loss prediction over irregular terrains based on parabolic equation // Journal of Radio Electronics. – 2012. – No. 1. (In Russian)
15. Lytaev M. S., Vladyko A. G. Split-step Padé approximations of the Helmholtz equation for radio coverage prediction over irregular terrain //2018 Advances in Wireless and Optical Communications (RTUWO). – IEEE, 2018. – pp. 179-184.
16. Lytaev M. S. Rational interpolation of the one-way Helmholtz propagator //Journal of Computational Science. – 2022. – Vol. 58.
17. Baydin A. G. è äð. Automatic differentiation in machine learning: a survey //Journal of machine learning research. – 2018. – Vol. 18. – No. 153. – pp. 1-43.
18. 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. – Vol. 70. – No. 3. – pp. 2137-2148.
19. Lytaev M. S. Numerov-Padé scheme for the one-way Helmholtz equation in tropospheric radio-wave propagation //IEEE Antennas and Wireless Propagation Letters. – 2020. – Vol. 19. – No. 12. – pp. 2167-2171.
20. Zhao X., Wang D. Ocean acoustic tomography from different receiver geometries using the adjoint method //The Journal of the Acoustical Society of America. – 2015. – Vol. 138. – No. 6. – pp. 3733-3741.
21. Mantzel W., Romberg J., Sabra K. Compressive matched-field processing //The Journal of the Acoustical Society of America. – 2012. – Vol. 132. – No. 1. – pp. 90-102.
22. Mecklenbräuker C. F., Gerstoft P. Objective functions for ocean acoustic inversion derived by likelihood methods //Journal of Computational Acoustics. – 2000. – Vol. 8. – No. 02. – pp. 259-270.
23. Liu D. C., Nocedal J. On the limited memory BFGS method for large scale optimization //Mathematical programming. – 1989. – Vol. 45. – No. 1. – pp. 503-528.
24. Marchuk G. I. Adjoint equations and analysis of complex systems. – Springer Science & Business Media, 2013.
25. Lin M. Automatic Functional Differentiation in JAX //The Twelfth International Conference on Learning Representations. – 2023.
26. Lytaev M. Automatically Differentiable Higher-Order Parabolic Equation for Real-Time Underwater Sound Speed Profile Sensing //Journal of Marine Science and Engineering. – 2024. – Vol. 12. – No. 11. – pp. 1925.
27. Xue T. è äð. JAX-FEM: A differentiable GPU-accelerated 3D finite element solver for automatic inverse design and mechanistic data science //Computer Physics Communications. – 2023. – Vol. 291.
28. Ataei M., Salehipour H. XLB: A differentiable massively parallel lattice Boltzmann library in Python //Computer Physics Communications. – 2024. – Vol. 300.
29. PyWaveProp. URL: https://github.com/mikelytaev/wave-propagation (accessed: 12.12.2024).
30. Scopatz A., Huff K.D. Effective computation in physics: Field guide to research with python. – O'Reilly Media, Inc., 2015.
31. Douvenot R. et al. A duct mapping method using least squares support vector machines //Radio Science. – 2008. – Vol. 43. – No. 06.
32. Lytaev M. Mesh optimization for the acoustic parabolic equation //Journal of Marine Science and Engineering. – 2023. – Vol. 11. – No. 3.
33. Lytaev M.S. Computational Grid Optimization for the 3D Higher-Order Parabolic Equation //International Conference on Computational Science and Its Applications. – Cham: Springer Nature Switzerland, 2023. – pp. 170-185.
For citation:
Lytaev M.S. Tropospheric refraction sensing using the automatic differentiation of the parabolic equation // Journal of Radio Electronics. – 2025. – ¹. 3. https://doi.org/10.30898/1684-1719.2025.3.11 (In Russian)