Modeling of Electromagnetically Induced Transparency With RLC Circuits and Metamaterial Cell

Ilchenko, M. E.; Zhivkov, A.; Камаралі, Роман; Lutchak, O. V.; Fedorchuk, Oleksandr; V’yunov, O. I.; Belous, A. G.; Plutenko, Tetiana; Аvdeyenko, G. L.

doi:10.1109/tmtt.2023.3275653

Cited by 8 publications

(1 citation statement)

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“…In addition, the presence of Fano- and electromagnetically induced transparency (EIT)-type transmission line shapes have been observed to produce high-quality (Q) factors, which are useful for high-sensitivity sensing in the development of sensors [ 14 ]. Currently, Fano resonances and EIT have demonstrated good resonance response in metamaterial units and square lattice plasma nanostructures [ 15 , 16 ]. Compared with the CS method, its low computational complexity reduces the cost of practical application.…”

Section: Introductionmentioning

confidence: 99%

A High-Resolution Imaging Method for Multiple-Input Multiple-Output Sonar Based on Deterministic Compressed Sensing

Gao,

Xu,

Yang

2024

Sensors

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Differences between conventional sonar and Multiple-Input Multiple-Output (MIMO) sonar systems arise in achieving high angular and range resolution. MIMO sonar uses Matched Filtering (MF) with well-correlated transmitted signals to enhance spatial resolution by obtaining virtual arrays. However, imperfect correlation characteristics yield high sidelobe values, which hinder accurate target localization in underwater imagery. To address this, a Compressed Sensing (CS) method is proposed by reconstructing echo signals to suppress correlation noise between orthogonal waveforms. A shifted dictionary matrix and a deterministic Discrete Fourier Transform (DFT) measurement matrix are used to multiply received echo signals to yield compressed measurements. A sparse recovery algorithm is applied to optimize signal reconstruction before joint transmit–receive beamforming forms a 2D sonar image in the angle-range domain. Numerical simulations and lake experimental results confirm the effectiveness of the proposed method, by obtaining a lower sidelobe sonar image under sub-Nyquist sampling rates as compared with other approaches.

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Section: Introductionmentioning

confidence: 99%