A three-dimensional target electromagnetic property perception method based on a reconfigurable intelligent surface

By optimizing the RIS scattering matrix and compressed sensing algorithm, the problems of high cross-correlation of measurement modes and low acquisition efficiency in RIS-assisted electromagnetic imaging were solved, and high-precision three-dimensional target electromagnetic property sensing and imaging were achieved.

CN122632255APending Publication Date: 2026-08-25NANJING UNIV OF POSTS & TELECOMM
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Patent Information

Application Number
CN202610668588.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-05-15
Publication Date
2026-08-25

AI Technical Summary

Technical Problem

Traditional reconfigurable smart surface (RIS)-assisted electromagnetic imaging methods suffer from high cross-correlation of measurement modes, difficulty in hardware implementation, and low acquisition efficiency.

Method used

A scattering coefficient matrix generation method based on mutual coherence optimization is adopted, combined with the method of moments and multi-objective Bayesian compressed sensing reconstruction algorithm, to construct an end-to-end electromagnetic propagation model, optimize the RIS scattering matrix configuration, and reconstruct the target electromagnetic properties through compressed sensing theory.

Benefits of technology

It improves the information independence and reconstruction stability of the measurement matrix, reduces the hardware implementation complexity, and realizes high-precision three-dimensional target electromagnetic property sensing and imaging, with high imaging accuracy and strong noise resistance.

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Abstract

The application relates to the technical field of electromagnetic imaging, in particular to a three-dimensional target electromagnetic property perception method based on a reconfigurable intelligent surface, which comprises the following steps: configuring parameters of an electromagnetic imaging system, generating RIS unit scattering coefficients based on mutual coherence optimization by adopting an MCBB algorithm; configuring the scattering coefficients on the RIS, scattering and reconstructing electromagnetic waves generated by a transmitting antenna; linearly correlating contrast parameters of a measurement target with received scattering field data by adopting a linear measurement model; and finally, inverting the target electromagnetic property by utilizing mt_cs. The application realizes high-precision inversion of the target electromagnetic property in the RIS-assisted imaging framework by optimizing and designing the super-surface reflection coefficient and constructing a measurement matrix with multi-dimensional low cross-correlation characteristics.
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