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Conference Papers Year : 2020

Imaging of a micro-structure: binary contrast source inversion and convolutional neural networks

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Abstract

Time-harmonic transverse-magnetic electromagnetic imaging of a grid-like, finite set of circular cylindrical dielectric rods placed in air with sub-wavelength distances between adjacent rods and sub-wavelength diameters is considered. It is shown how one can be achieving super-resolution in the resulting micro-structure, reaching beyond the Rayleigh criterion, using a binary-specialized form of teh contrast source inversion method and another method based on convolutional neural networks. illustrations of both methods are proposed from comprehensive numerical simulations in a number of configurations of interest, this seen in terms of organization of the micro-structure itself, discrete frequencies of observation, data acquisition and data noise. Experimental validations are proposed as well from experiments carried outt in an anechoic chamber.
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Dates and versions

hal-02906373 , version 1 (30-08-2020)

Identifiers

  • HAL Id : hal-02906373 , version 1

Cite

Peipei Ran, Yingying Qin, Dominique Lesselier, Mohammed Serhir. Imaging of a micro-structure: binary contrast source inversion and convolutional neural networks. XXXIII General Assembly and Scientific Symposium (GASS) of the International Union of Radio Science, Aug 2020, Rome, Italy. pp.B06-02. ⟨hal-02906373⟩
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