Dynamic Metasurface Antenna-Based Mills-Cross Aperture for 3-D Computational Microwave Imaging

Álvarez-Narciandi, Guillermo; García-Fernández, María; Skouroliakou, Vasiliki; Yurduseven, Okan

doi:10.1109/lawp.2024.3416899

Cited by 3 publications

References 34 publications

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A Measurement Mode Selection Method for Computational Microwave Imaging

Li,

Zhao,

Abbasi

et al. 2024

Antennas Wirel. Propag. Lett.

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This paper introduces a novel method for selecting useful measurement modes in computational microwave imaging (CMI) systems utilizing metasurface antennas. With the aim of improving the computational efficiency without compromising the imaging quality, a regional average correlation matrix (RACM) that can evaluate the quality of measurement modes based on an area-specific analysis of the near-field distributions is firstly proposed. Building upon the RACM, an algorithm known as the contribution matrix sorting (CMS) is subsequently developed to filter useful measurement modes based on their contributions to the CMI. By implementing this selection method, the paper demonstrates the potential for significantly improving the CMI computation efficiency. The effectiveness of this approach is validated through full-wave simulations in CST Microwave Studio, showing that the quality of reconstructed images can be maintained even when the number of measurement modes is reduced by as much as 76%. This work presents a significant step forward in the practical application of metasurface-based CMI systems, offering a method to tackle the challenges of computational efficiency while ensuring high-quality imaging outcomes.

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A Measurement Mode Selection Method for Computational Microwave Imaging

Li,

Zhao,

Abbasi

et al. 2024

Antennas Wirel. Propag. Lett.

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Generative model-based image reconstruction from back-scattered data in computational microwave imaging

Zhang,

Sharma

et al. 2024

Sensors and Communication Technologies in the 1 GHz to 10 THz Band

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Conventional microwave imaging can provide high-quality reconstructed images, but is also limited by the increased hardware complexity and a slow data acquisition speed. Although computational imaging (CI)-based systems are developed to be alternatives, they may require substantial computational power and time. To reduce the hardware complexity and computational burden associated with scene reconstructions of CI applications, in this paper, a conditional generative adversarial network (cGAN) is presented to achieve image reconstruction, where the back-scattered measurement is regarded as both the condition and the input of the proposed network. With testing dataset, the average values of the normalized mean squared error (NMSE) and the normalized mean absolute error (NMAE) are 0.0474 and 0.2267, respectively. In addition, a noise analysis is conducted, showing the reliability of the proposed network in noisy settings.

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Multistatic 3-D microwave imaging with dynamic metasurface antennas: a Fourier-based approach

Molaei,

Fromenteze,

Skouroliakou

et al. 2024

Sensors and Communication Technologies in the 1 GHz to 10 THz Band

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This paper proposes a novel approach to 3-D microwave imaging using dynamic metasurface antennas in a multistatic configuration. By introducing a panel-to-panel model and a preprocessing technique, raw measurements are converted into the space-frequency domain for efficient data acquisition and reconstruction. Adapting the range migration algorithm in this work enables fast Fourier-based image reconstruction. Simulation results showcase the effectiveness of the proposed method, highlighting its potential for real-world applications.

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Dynamic Metasurface Antenna-Based Mills-Cross Aperture for 3-D Computational Microwave Imaging

Cited by 3 publications

References 34 publications

A Measurement Mode Selection Method for Computational Microwave Imaging

A Measurement Mode Selection Method for Computational Microwave Imaging

Generative model-based image reconstruction from back-scattered data in computational microwave imaging

Multistatic 3-D microwave imaging with dynamic metasurface antennas: a Fourier-based approach

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