Fourier Compatible Near-Field Multiple-Input Multiple-Output Terahertz Imaging With Sparse Non-Uniform Apertures
Among image reconstruction methods, Fourier transform-based techniques provide computationally better performance. However, conventional Fourier-based reconstruction techniques require uniform data sampling at the radar aperture. In this paper, a multiple-input multiple-output (MIMO) scenario for ne...
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IEEE
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/245d822431d942b2a210cdf825329557 |
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| Sumario: | Among image reconstruction methods, Fourier transform-based techniques provide computationally better performance. However, conventional Fourier-based reconstruction techniques require uniform data sampling at the radar aperture. In this paper, a multiple-input multiple-output (MIMO) scenario for near-field (NF) terahertz imaging systems is considered. A compressive-sensing-based method compatible with efficient fast Fourier-based techniques for image reconstruction is proposed. To reduce the error due to the multistatic array topology in the NF, a multistatic-to-monostatic conversion is used. Employing the proposed method significantly reduces the number of antennas and channels. This, in addition to saving hardware resources, can improve the overall performance of the system depending on the type of channel access scheme. The results based on both numerical and electromagnetic data, presented as reconstructed images of the scene, confirm the performance of the proposed method. |
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