Research article

On the identification of small anomaly in microwave imaging without homogeneous background information

  • Received: 25 July 2023 Revised: 07 September 2023 Accepted: 18 September 2023 Published: 25 September 2023
  • MSC : 78A46

  • For a successful application of subspace migration algorithm to retrieve the exact location and shape of small anomaly in microwave imaging, one must begin the reconstruction process under the assumption that complete information about the homogeneous background medium, such as background permittivity and conductivity, is available. In many studies, the statistical value of the background medium was adopted, raising the possibility of an incorrect value being applied. Thus, simulation results have been examined in order to identify cases in which an inaccurate location and shape of anomaly were retrieved. However, the theory explaining this phenomenon has not been investigated. In this paper, we apply an alternative wavenumber instead of the true one and identify the mathematical structure of the subspace migration imaging function for retrieving two-dimensional small anomaly by establishing a relationship with an infinite series of Bessel functions of the first kind. The revealed structure explains the reason behind the retrieval of an inaccurate location and shape of anomaly. The simulation results with synthetic data are presented to support the theoretical result.

    Citation: Won-Kwang Park. On the identification of small anomaly in microwave imaging without homogeneous background information[J]. AIMS Mathematics, 2023, 8(11): 27210-27226. doi: 10.3934/math.20231392

    Related Papers:

  • For a successful application of subspace migration algorithm to retrieve the exact location and shape of small anomaly in microwave imaging, one must begin the reconstruction process under the assumption that complete information about the homogeneous background medium, such as background permittivity and conductivity, is available. In many studies, the statistical value of the background medium was adopted, raising the possibility of an incorrect value being applied. Thus, simulation results have been examined in order to identify cases in which an inaccurate location and shape of anomaly were retrieved. However, the theory explaining this phenomenon has not been investigated. In this paper, we apply an alternative wavenumber instead of the true one and identify the mathematical structure of the subspace migration imaging function for retrieving two-dimensional small anomaly by establishing a relationship with an infinite series of Bessel functions of the first kind. The revealed structure explains the reason behind the retrieval of an inaccurate location and shape of anomaly. The simulation results with synthetic data are presented to support the theoretical result.



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    [1] S. Ahmad, T. Strauss, S. Kupis, T. Khan, Comparison of statistical inversion with iteratively regularized Gauss Newton method for image reconstruction in electrical impedance tomography, Appl. Math. Comput., 358 (2019), 436–448. https://doi.org/10.1016/j.amc.2019.03.063 doi: 10.1016/j.amc.2019.03.063
    [2] M. N. Akinci, Improving near-field orthogonality sampling method for qualitative microwave imaging, IEEE T. Antenna. Propag., 66 (2018), 5475–5484. https://doi.org/10.1109/TAP.2018.2860123 doi: 10.1109/TAP.2018.2860123
    [3] H. Ammari, P. Garapon, F. Jouve, H. Kang, M. Lim, S. Yu, A new optimal control approach for the reconstruction of extended inclusions, SIAM J. Control Optim., 51 (2013), 1372–1394. https://doi.org/10.1137/100808952 doi: 10.1137/100808952
    [4] H. Ammari, J. Garnier, H. Kang, W. K. Park, K. Sølna, Imaging schemes for perfectly conducting cracks, SIAM J. Appl. Math., 71 (2011), 68–91. https://doi.org/10.1137/100800130 doi: 10.1137/100800130
    [5] H. Ammari, E. Iakovleva, S. Moskow, Recovery of small inhomogeneities from the scattering amplitude at a fixed frequency, SIAM J. Math. Anal., 34 (2003), 882–900. https://doi.org/10.1137/S0036141001392785 doi: 10.1137/S0036141001392785
    [6] H. Ammari, S. Moskow, M. Vogelius, Boundary integral formulas for the reconstruction of electromagnetic imperfections of small diameter, ESAIM Control Optim. Ca., 9 (2003), 49–66. https://doi.org/10.1051/cocv:2002071 doi: 10.1051/cocv:2002071
    [7] H. Ammari, M. Vogelius, D. Volkov, Asymptotic formulas for perturbations in the electromagnetic fields due to the presence of imperfections of small diameter II. the full {M}axwell equations, J. Math. Pure. Appl., 80 (2001), 769–814. https://doi.org/10.1016/S0021-7824(01)01217-X doi: 10.1016/S0021-7824(01)01217-X
    [8] L. Audibert, H. Haddar, The generalized linear sampling method for limited aperture measurements, SIAM J. Imaging Sci., 10 (2017), 845–870. https://doi.org/10.1137/16M110112X doi: 10.1137/16M110112X
    [9] L. Borcea, G. Papanicolaou, F. G. Vasquez, Edge illumination and imaging of extended reflectors, SIAM J. Imaging Sci., 1 (2008), 75–114. https://doi.org/10.1137/07069290X doi: 10.1137/07069290X
    [10] Y. Boukari, H. Haddar, The factorization method applied to cracks with impedance boundary conditions, Inverse Probl. Imag., 7 (2013), 1123–1138. https://doi.org/10.3934/ipi.2013.7.1123 doi: 10.3934/ipi.2013.7.1123
    [11] A. E. Bulyshev, S. Y. Semenov, A. E. Souvorov, R. H. Svenson, A. G. Nazarov, Y. E. Sizov, et al., Computational modeling of three-dimensional microwave tomography of breast cancer, IEEE T. Bio-Med. Eng., 48 (2001), 1053–1056. https://doi.org/10.1109/10.942596 doi: 10.1109/10.942596
    [12] R. Chandra, H. Zhou, I. Balasingham, R. M. Narayanan, On the opportunities and challenges in microwave medical sensing and imaging, IEEE T. Bio.-Med. Eng., 62 (2015), 1667–1682. https://doi.org/10.1109/TBME.2015.2432137 doi: 10.1109/TBME.2015.2432137
    [13] W. C. Chew, Y. M. Wang, Reconstruction of two-dimensional permittivity distribution using the distorted born iterative method, IEEE T. Med. Imaging, 9 (1990), 218–225. https://doi.org/10.1109/42.56334 doi: 10.1109/42.56334
    [14] D. Colton, R. Kress, Inverse acoustic and electromagnetic scattering problems, Mathematics and Applications Series, New York: Springer, 1998. https://doi.org/10.1007/978-1-4614-4942-3
    [15] H. Diao, X. Cao, H. Liu, On the geometric structures of transmission eigenfunctions with a conductive boundary condition and applications, Commun. Part. Diff. Eq., 46 (2021), 630–679. https://doi.org/10.1080/03605302.2020.1857397 doi: 10.1080/03605302.2020.1857397
    [16] O. Dorn, D. Lesselier, Level set methods for inverse scattering, Inverse Probl., 22 (2006), R67–R131. https://doi.org/10.1088/0266-5611/22/4/R01 doi: 10.1088/0266-5611/22/4/R01
    [17] A. Franchois, C. Pichot, Microwave imaging-complex permittivity reconstruction with a Levenberg-Marquardt method, IEEE T. Antenn. Propag., 45 (1997), 203–215. https://doi.org/10.1109/8.560338 doi: 10.1109/8.560338
    [18] N. I. Grinberg, A. Kirsch, The factorization method for obstacles with a-priori separated sound-soft and sound-hard parts, Math. Comput. Simulat., 66 (2004), 267–279. https://doi.org/10.1016/j.matcom.2004.02.011 doi: 10.1016/j.matcom.2004.02.011
    [19] M. Haynes, J. Stang, M. Moghaddam, Real-time microwave imaging of differential temperature for thermal therapy monitoring, IEEE T. Bio.-Med. Eng., 61 (2014), 1787–1797. https://doi.org/10.1109/TBME.2014.2307072 doi: 10.1109/TBME.2014.2307072
    [20] D. Ireland, K. Bialkowski, A. Abbosh, Microwave imaging for brain stroke detection using Born iterative method, IET Microw. Antenna. P., 7 (2013), 909–915. https://doi.org/10.1049/iet-map.2013.0054 doi: 10.1049/iet-map.2013.0054
    [21] N. Irishina, O. Dorn, M. Moscoso, A level set evolution strategy in microwave imaging for early breast cancer detection, Comput. Math. Appl., 56 (2008), 607–618. https://doi.org/10.1016/j.camwa.2008.01.004 doi: 10.1016/j.camwa.2008.01.004
    [22] K. Ito, B. Jin, J. Zou, A direct sampling method to an inverse medium scattering problem, Inverse Probl., 28 (2012), 025003. https://doi.org/10.1088/0266-5611/28/2/025003 doi: 10.1088/0266-5611/28/2/025003
    [23] S. Kang, M. Lambert, W. K. Park, Direct sampling method for imaging small dielectric inhomogeneities: Analysis and improvement, Inverse Probl., 34 (2018), 095005. https://doi.org/10.1088/1361-6420/aacf1d doi: 10.1088/1361-6420/aacf1d
    [24] A. Kirsch, S. Ritter, A linear sampling method for inverse scattering from an open arc, Inverse Probl., 16 (2000), 89–105. https://doi.org/10.1088/0266-5611/16/1/308 doi: 10.1088/0266-5611/16/1/308
    [25] O. Kwon, J. K. Seo, J. R. Yoon, A real-time algorithm for the location search of discontinuous conductivities with one measurement, Commun. Pur. Appl. Math., 55 (2002), 1–29. https://doi.org/10.1002/cpa.3009 doi: 10.1002/cpa.3009
    [26] Z. Liu, A new scheme based on Born iterative method for solving inverse scattering problems with noise disturbance, IEEE Geosci. Remote S., 16 (2019), 1021–1025. https://doi.org/10.1109/LGRS.2019.2891660 doi: 10.1109/LGRS.2019.2891660
    [27] F. L. Louër, M. L. Rapún, Topological sensitivity for solving inverse multiple scattering problems in 3D electromagnetism. Part I: One step method, SIAM J. Imaging Sci., 10 (2017), 1291–1321. https://doi.org/10.1137/17M1113850 doi: 10.1137/17M1113850
    [28] R. Palmeri, M. T. Bevacqua, L. Crocco, T. Isernia, L. D. Donato, Microwave imaging via distorted iterated virtual experiments, IEEE T. Antenn. Propag., 65 (2017), 829–838. https://doi.org/10.1109/TAP.2016.2633070 doi: 10.1109/TAP.2016.2633070
    [29] W. K. Park, Multi-frequency subspace migration for imaging of perfectly conducting, arc-like cracks in full- and limited-view inverse scattering problems, J. Comput. Phys., 283 (2015), 52–80. http://dx.doi.org/10.1016/j.jcp.2014.11.036 doi: 10.1016/j.jcp.2014.11.036
    [30] W. K. Park, A novel study on subspace migration for imaging of a sound-hard arc, Comput. Math. Appl., 74 (2017), 3000–3007. http://dx.doi.org/10.1016/j.camwa.2017.07.045 doi: 10.1016/j.camwa.2017.07.045
    [31] W. K. Park, Performance analysis of multi-frequency topological derivative for reconstructing perfectly conducting cracks, J. Comput. Phys., 335 (2017), 865–884.
    [32] W. K. Park, Real-time microwave imaging of unknown anomalies via scattering matrix, Mech. Syst. Signal Pr., 118 (2019), 658–674. https://doi.org/10.1016/j.ymssp.2018.09.012 doi: 10.1016/j.ymssp.2018.09.012
    [33] W. K. Park, Experimental validation of the factorization method to microwave imaging, Results Phys., 17 (2020), 103071. https://doi.org/10.1016/j.rinp.2020.103071 doi: 10.1016/j.rinp.2020.103071
    [34] W. K. Park, Application of MUSIC algorithm in real-world microwave imaging of unknown anomalies from scattering matrix, Mech. Syst. Signal Pr., 153 (2021), 107501. https://doi.org/10.1016/j.ymssp.2020.107501 doi: 10.1016/j.ymssp.2020.107501
    [35] W. K. Park, A novel study on the MUSIC-type imaging of small electromagnetic inhomogeneities in the limited-aperture inverse scattering problem, J. Comput. Phys., 460 (2022), 111191. https://doi.org/10.1016/j.jcp.2022.111191 doi: 10.1016/j.jcp.2022.111191
    [36] W. K. Park, Real-time detection of small anomaly from limited-aperture measurements in real-world microwave imaging, Mech. Syst. Signal Pr., 171 (2022), 108937. https://doi.org/10.1016/j.ymssp.2022.108937 doi: 10.1016/j.ymssp.2022.108937
    [37] W. K. Park, On the application of orthogonality sampling method for object detection in microwave imaging, IEEE T. Antenn. Propag., 71 (2023), 934–946. https://doi.org/10.1109/TAP.2022.3220033 doi: 10.1109/TAP.2022.3220033
    [38] W. K. Park, H. P. Kim, K. J. Lee, S. H. Son, MUSIC algorithm for location searching of dielectric anomalies from ${S}$-parameters using microwave imaging, J. Comput. Phys., 348 (2017), 259–270. http://dx.doi.org/10.1016/j.jcp.2017.07.035 doi: 10.1016/j.jcp.2017.07.035
    [39] W. K. Park, D. Lesselier, Reconstruction of thin electromagnetic inclusions by a level set method, Inverse Probl., 25 (2009), 085010. https://doi.org/10.1088/0266-5611/25/8/085010 doi: 10.1088/0266-5611/25/8/085010
    [40] R. Potthast, A study on orthogonality sampling, Inverse Probl., 26 (2010), 074015. https://doi.org/10.1088/0266-5611/26/7/074015 doi: 10.1088/0266-5611/26/7/074015
    [41] D. M. Pozar, Microwave engineering, 4 Eds., John Wiley & Sons, 2011.
    [42] M. Slaney, A. C. Kak, L. E. Larsen, Limitations of imaging with first-order diffraction tomography, IEEE T. Microw. Theory, 32 (1984), 860–874. https://doi.org/10.1109/TMTT.1984.1132783 doi: 10.1109/TMTT.1984.1132783
    [43] S. H. Son, K. J. Lee, W. K. Park, Application and analysis of direct sampling method in real-world microwave imaging, Appl. Math. Lett., 96 (2019), 47–53. https://doi.org/10.1016/j.aml.2019.04.016 doi: 10.1016/j.aml.2019.04.016
    [44] S. H. Son, N. Simonov, H. J. Kim, J. M. Lee, S. I. Jeon, Preclinical prototype development of a microwave tomography system for breast cancer detection, ETRI J., 32 (2010), 901–910. https://doi.org/10.4218/etrij.10.0109.0626 doi: 10.4218/etrij.10.0109.0626
    [45] A. Timonov, M. V. Klibanov, A new iterative procedure for the numerical solution of coefficient inverse problems, Appl. Numer. Math., 55 (2005), 191–203. https://doi.org/10.1016/j.apnum.2004.09.031 doi: 10.1016/j.apnum.2004.09.031
    [46] W. Yin, H. Qi, P. Meng, Broad learning system with preprocessing to recover the scattering obstacles with far-field data, Adv. Appl. Math. Mech., 15 (2023), 984–1000. https://doi.org/10.4208/aamm.OA-2021-0352 doi: 10.4208/aamm.OA-2021-0352
    [47] Y. Yin, W. Yin, P. Meng, H. Liu, The interior inverse scattering problem for a two-layered cavity using the bayesian method, Inverse Probl. Imag., 16 (2022), 673–690. https://doi.org/10.3934/ipi.2021069 doi: 10.3934/ipi.2021069
    [48] D. Zhang, Y. Guo, Y. Wang, Y. Chang, Co-inversion of a scattering cavity and its internal sources: Uniqueness, decoupling and imaging, Inverse Probl., 39 (2023), 065004. https://doi.org/10.1088/1361-6420/accc4f doi: 10.1088/1361-6420/accc4f
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