Abstract
This note is concerned with inverse wave scattering in one and two dimensional domains. It seeks to recover an unknown function based on measurements collected at the boundary of the domain. For one-dimensional problem, only one point of the domain is assumed to be accessible. For the two dimensional domain, the outer boundary is assumed to be accessible. It develops two iterative algorithms, in which an assumed initial guess for the unknown function is updated. The first method uses a set of sampling functions to formulate a moment problem for the correction to the assumed value. This method is applied to both one-dimensional and two dimensional domains. For two dimensional Helmholtz equation, it relies on a new effective filtering technique which is another contribution of the present work. The second method uses a direct formulation to recover the correction term. This method is only developed for the one-dimensional case. For all cases presented here, the correction to the assumed value is obtained by solving an over-determined linear system through the use of least-square minimization. Tikhonov regularization is also used to stabilize the least-square solution. A number of numerical examples are used to show their applicability and robustness to noise.
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Notes
Note that, for nonzero \({\hat{u}}(x)\), the kernel functions \(e^{ik_1(\eta -2)}\) and \(e^{ik_2(\eta -2)}\) are linearly independent in [0 : 2] for \(k_1\ne k_2\).
The Helmholtz equation in Eq. (31) is well-posed for \(k^2\) away from the eigenvalues of the Laplace operator. Therefore, \(\xi _i({\mathbf{x}})\) and \(\xi _j({\mathbf{x}})\) are linearly independent for two linearly independent boundary conditions i.e., \(\varpi _i({\mathbf{x}})\) and \(\varpi _j({\mathbf{x}})\), \({\mathbf{x}}\in {\partial }\varOmega \).
In actuality, the functions \(\varepsilon _j({\mathbf{x}})\) should satisfy the nonhomogeneous Helmholtz equation given by \(\varDelta \varepsilon _j+k^2p({\mathbf{x}})\varepsilon +\chi _j({\mathbf{x}})=0\). However, at this stage \(p({\mathbf{x}})\) is unknown, and we are using \({\hat{p}}({\mathbf{x}})\) instead. As the iteration proceeds, \({\hat{p}}({\mathbf{x}})\) converges to \(p({\mathbf{x}})\).
References
Ang DD, Gorenflo R, Le Khoi V, Trong DD (2002) Moment theory and some inverse problems in potential theory and heat conduction. Springer
Barcelo JA, Castro C, Reyes JM (2016) Numerical approximation of the potential in the two-dimensional inverse scattering problems. Inverse Problems 32:015006
Belai V, Frumin LL, Podivilov EV, Shapiro DA (2008) Inverse scattering for the one-dimensional Helmholtz equation: fast numerical method. Opt Lett 33(18):2101–2103
Bugarija S, Gibson PC, Hu G, Li P, Zhao Y (2020) Inverse scattering for the one-dimensional Helmholtz equation with piecewise constant wave speed. Inverse Problems 36(7):075008
Capozzoli A, Curcio C, Liseno A (2017) Singular value optimization in inverse electromagnetic scattering. IEEE Antennas Wirel Propag Lett 16:1094–1097
Christensen O (2010) Functions, spaces, and expansions. Springer, New York
Colten D, Kress R (1991) Inverse acoustic and electromagetic scattering theory. Springer, New York
Colten D, Coyle J, Monk P (2000) Recent developments in inverse acoustic scattering theory. SIAM Rev 42(3):369–414
Creedon DL, Tobar ME, Ivanov EN, Hartnett JN (2011) High-resolution Flicker-noise-free frequency measurements of weak microwave signals. IEEE Trans Microw Theory Techn 59(6):1651–1657
Desmal A, Bağci H (2015) A preconditioned inexact Newton method for nonlinear sparse electromagnetic imaging. IEEE Geosci Rem Sens Lett 12(3):532–536
Eshkuvatov Z (2018) Homotopy perturbation method and Chebyshev polynomials for solving a class of singular and hypersingular integral equations. Numer Algebra Control Optim 8(3):347–360
Fessler JA (2010) Model-based image reconstruction for MRI. IEEE Signal Process Mag 27(4):81–89
Hamad A, Tadi M (2019) Inverse scattering based on proper solution space. J Theor Comput Acoust 27(3):1850033
Irishina N, Dorn O, Moscoso M (2008) A level set evolution strategy in microwave imaging for early breast cancer. Comput Math Appl 56:607–618
Jin B, Zheng Y (2006) A meshless method for some inverse problems associated with the Helmholtz equation. Comput Methods Appl Mech Eng 195:2270–2288
Jamil M, Hassan MK, Al-Mattarneh MA, Zain MFM (2013) Concrete dielectric properties investigation using microwave nondestructive techniques. Mater Struct 46(1):77–87
Kang S, Lambert M, Ahn CY, Ha T, Park W-K (2020) Single- and multi-frequency direct sampling methods in limited-aperture inverse scattering problem. IEEE Access 8:121637–121649
Klibanov MV, Kolesov A, Sullivan A, Nguyen LD (2018) A new version of the convexification method for a 1D coefficient inverse problem with experimental data. Inverse Problems 34(11):115014
Klibanov MV, Romanov VG (2015) Two reconstruction procedures for a 3D phaseless inverse scattering problem for the generalized Helmholtz equation. Inverse Problems 32:015005
Lagaris IE, Evangelakis GA (2011) One-dimensional inverse scattering problem in acoustics. Brazil J Phys 41:248–257
Lay D, Lay S, McDonald J (2016) Linear Algebra and its applications. Pearson, New York
Marin L, Elliott L, Heggs PJ, Ingham DB, Lesnic D, Wen X (2006) Dual reciprocity boundary element method solution of the Cauchy problem for Helmholtz-type equations with variable coefficients. J Sound Vib 297:89–105
Mueller JL, Siltanen S (2012) Linear and nonlinear inverse problems with practical applications. SIAM, Philadelphia
Novikov RG (2015) An iterative approach to non-overdetermined inverse scattering at fixed energy. Sbornik Math 206(1):120–134
Sacks P, Jaemin Shin (2009) Computational methods for some inverse scattering problems. Appl Math Comput 207:111–123
Tadi M (2017) On elliptic inverse heat conduction problems. ASME J Heat Tranasf 139(074504–1):4
Tadi M (2019) A direct method for a Cauchy problem with application to a Tokamak. Theor Appl Mech Lett 9(4):254–259
Tadi M, Nandakumaran AK, Sritharan SS (2011) An inverse problem for Helmholtz equation. Inverse Problems Sci Eng 19(6):839–854
Tadi M (2009) A computational method for an inverse problem in optical tomography. Discret Contin Dyn Syst-B 12(1):205–214
Thanh NT, Klibanov MV (2020) Solving a 1-D inverse medium scattering problem using a new multi-frequency globally strictly convex objective functional. J Inverse Ill-posed Problems 28(5):693–711
Zhang Z, Chen S, Xu Z, He Y, Li S (2017) Iterative regularization method in generalized inverse beamforming. J Sound Vib 396:108–121
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Appendix
Appendix
To obtain an approximate solution for the Helmholtz equation in Eq. (39) we can rewrite it according to
where \(\bar{p}({\mathbf{x}})={\hat{p}}({\mathbf{x}})-1\). We can then consider a similar perturbation approximation and obtain the solution as a series given by \(\xi =\xi ^0+\xi ^1+\xi ^2+\xi ^3+\dots \) where
Note that \(\hat{p}({\mathbf{x}})\) is zero for most of the region, and the above series converges very fast. In all calculations presented here, we are including four terms in the series.
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Tadi, M., Radenkovic, M. New computational methods for inverse wave scattering with a new filtering technique. Optim Eng 22, 2457–2479 (2021). https://doi.org/10.1007/s11081-021-09638-8
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DOI: https://doi.org/10.1007/s11081-021-09638-8