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Numerical Verification of the Convexification Method for a Frequency-Dependent Inverse Scattering Problem with Experimental Data

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Abstract

The reconstruction of physical properties of a medium from boundary measurements, known as inverse scattering problems, presents significant challenges. The present study aims to validate a newly developed convexification method for a 3D coefficient inverse problem in the case of buried unknown objects in a sandbox, using experimental data collected by a microwave scattering facility at The University of North Carolina at Charlotte. Our study considers the formulation of a coupled quasilinear elliptic system based on multiple frequencies. The system can be solved by minimizing a weighted Tikhonov-like functional, which forms our convexification method. Theoretical results related to the convexification are also revisited in this work.

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REFERENCES

  1. Clipper Controls Inc. 2020 Dielectric Constants of Various Materials. http://clippercontrols.com/pages/Dielectric-Constant-Values.html#W .

  2. A. D. Agaltsov, T. Hohage, and R. G. Novikov, “An iterative approach to monochromatic phaseless inverse scattering,” Inverse Probl. 35 (2), 024001 (2018).

    Article  ADS  MathSciNet  Google Scholar 

  3. N. V. Alekseenko, V. A. Burov, and O. D. Rumyantseva, “Solution of the three-dimensional acoustic inverse scattering problem. The modified Novikov algorithm,” Acoust. Phys. 54 (3), 407–419 (2008).

    Article  ADS  Google Scholar 

  4. A. B. Bakushinskii and A. S. Leonov, “Numerical solution of an inverse multifrequency problem in scalar acoustics,” Comput. Math. Math. Phys. 60 (6), 987–999 (2020).

    Article  MathSciNet  Google Scholar 

  5. E. Banks, Anti-Personnel Landmines: Recognising & Disarming (Brassey’s Essential Guides) (Potomac Books, , 1997).

  6. L. Beilina and M. V. Klibanov, Approximate Global Convergence and Adaptivity for Coefficient Inverse Problems (Springer, New York, 2012).

    Book  Google Scholar 

  7. A. L. Bukhgeim and M. V. Klibanov, “Global uniqueness of a class of multidimensional inverse problems,” Dokl. Akad. Nauk SSSR 260 (2), 269–272 (1981) [Sov. Math. Dokl. 24 (2), 244–247 (1981)].

    Google Scholar 

  8. G. Chavent, Nonlinear Least Squares for Inverse Problems (Springer Sci. + Bus. Media, New York, 2010).

    Book  Google Scholar 

  9. D. Colton and R. Kress, Inverse Acoustic and Electromagnetic Scattering Theory (Springer, Berlin–Heidelberg, 1992).

    Book  Google Scholar 

  10. D. J. Daniels, “A review of GPR for landmine detection,” Sens. Imaging: Int. J. 7 (3), 90–123 (2006).

    Article  ADS  Google Scholar 

  11. A. V. Goncharsky and S. Y. Romanov, “A method of solving the coefficient inverse problems of wave tomography,” Comput. Math. Appl. 77 (4), 967–980 (2019).

    Article  MathSciNet  Google Scholar 

  12. A. V. Goncharsky, S. Y. Romanov, and S. Y. Seryozhnikov, “Low-frequency ultrasonic tomography: Mathematical methods and experimental results,” Moscow Univ. Phys. Bull. 74 (1), 43–51 (2019).

    Article  ADS  Google Scholar 

  13. V. A. Khoa, G. W. Bidney, M. V. Klibanov, L. H. Nguyen, L. H. Nguyen, A. J. Sullivan, and V. N. Astratov, “Convexification and experimental data for a 3D inverse scattering problem with the moving point source,” Inverse Probl. 36 (8), 085007 (2020).

    Article  ADS  MathSciNet  Google Scholar 

  14. V. A. Khoa, G. W. Bidney, M. V. Klibanov, L. H. Nguyen, L. H. Nguyen, A. J. Sullivan, and V. N. Astratov, “An inverse problem of a simultaneous reconstruction of the dielectric constant and conductivity from experimental backscattering data,” Inverse Probl. Sci. Eng. 29 (5), 712–735 (2020).

    Article  MathSciNet  Google Scholar 

  15. V. A. Khoa, M. V. Klibanov, and L. H. Nguyen, “Convexification for a three-dimensional inverse scattering problem with the moving point source,” SIAM J. Imaging Sci. 13 (2), 871–904 (2020).

    Article  MathSciNet  Google Scholar 

  16. M. V. Klibanov, “Carleman estimates for global uniqueness, stability and numerical methods for coefficient inverse problems,” J. Inverse Ill-Posed Probl. 21 (4) (2013).

  17. M. V. Klibanov, “Convexification of restricted Dirichlet-to-Neumann map,” J. Inverse Ill-Posed Probl. 25 (5) (2017).

  18. M. V. Klibanov, V. A. Khoa, A. V. Smirnov, L. H. Nguyen, G. W. Bidney, L. H. Nguyen, A. J. Sullivan, and V. N. Astratov, “Convexification inversion method for nonlinear SAR imaging with experimentally collected data,” J. Appl. Ind. Math. 15 (3), 413–436 (2021).

    Article  MathSciNet  Google Scholar 

  19. M. V. Klibanov, A. E. Kolesov, A. Sullivan, and L. Nguyen, “A new version of the convexification method for a 1D coefficient inverse problem with experimental data,” Inverse Probl. 34 (11), 115014 (2018).

    Article  ADS  MathSciNet  Google Scholar 

  20. M. V. Klibanov and J. Li, Inverse Problems and Carleman Estimates Global Uniqueness, Global Convergence and Experimental Data (de Gruyter, Berlin, 2021).

    Book  Google Scholar 

  21. M. V. Klibanov, J. Li, and W. Zhang, “Numerical solution of the 3-D travel time tomography problem,” J. Comput. Phys. 476, 111910 (2023).

    Article  MathSciNet  Google Scholar 

  22. A. V. Kuzhuget, L. Beilina, M. V. Klibanov, A. Sullivan, L. Nguyen, and M. A. Fiddy, “Blind backscattering experimental data collected in the field and an approximately globally convergent inverse algorithm,” Inverse Probl. 28 (9), 095007 (2012).

    Article  ADS  Google Scholar 

  23. A. V. Kuzhuget and M. V. Klibanov, “Global convergence for a 1-D inverse problem with application to imaging of land mines,” Appl. Anal. 89 (1), 125–157 (2010).

    Article  MathSciNet  Google Scholar 

  24. T. T. Le and L. H. Nguyen, “The gradient descent method for the convexification to solve boundary value problems of quasilinear PDEs and a coefficient inverse problem,” J. Sci. Comput. 91 (3) (2022).

  25. T. T. T. Le and L. H. Nguyen, “A convergent numerical method to recover the initial condition of nonlinear parabolic equations from lateral Cauchy data,” J. Inverse and Ill-Posed Probl. 30 (2), 265–286 (2020).

    Article  MathSciNet  Google Scholar 

  26. D.-L. Nguyen, M. V. Klibanov, L. H. Nguyen, and M. A. Fiddy, “Imaging of buried objects from multi-frequency experimental data using a globally convergent inversion method,” J. Inverse and Ill-Posed Probl. 26 (4), 501–522 (2017).

    Article  MathSciNet  Google Scholar 

  27. R. G. Novikov, “An iterative approach to non-overdetermined inverse scattering at fixed energy,” Sb.: Math. 206 (1), 120–134 (2015).

    MathSciNet  Google Scholar 

  28. “Office of the Chief of Ordnance. Catalog of enemy ordnance materiel,” in World War II Operational Documents, no. N2228-E, 1945. http://cgsc.contentdm.oclc.org/cdm/ref/collection/p4013coll8/id/2758 .

  29. B. T. Polyak, Introduction to Optimization (Optim. Software, Publ. Div., 1987).

  30. Nguyen Trung Thành, L. Beilina, M. V. Klibanov, and Mi. A. Fiddy, “Imaging of buried objects from experimental backscattering time-dependent measurements using a globally convergent inverse algorithm,” SIAM J. Imaging Sci. 8 (1), 757–786 (2015).

    Article  MathSciNet  Google Scholar 

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ACKNOWLEDGMENTS

V. A. Khoa thanks Dr. Darin Ragozzine (Brigham Young University, USA) for the recent support of his research career.

Funding

V. A. Khoa was supported by NSF grant no. DMS-2316603. L. H. Nguyen was supported by NSF Grant no. DMS-2208159.

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Correspondence to T. Le, V. A. Khoa, M. V. Klibanov, L. H. Nguyen, G. W. Bidney or V. N. Astratov.

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CONFLICT OF INTEREST. The authors of this work declare that they have no conflicts of interest.

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Le, T., Khoa, V.A., Klibanov, M.V. et al. Numerical Verification of the Convexification Method for a Frequency-Dependent Inverse Scattering Problem with Experimental Data. J. Appl. Ind. Math. 17, 908–927 (2023). https://doi.org/10.1134/S199047892304018X

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  • DOI: https://doi.org/10.1134/S199047892304018X

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