Abstract
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.
Highlights
In recent years, active terahertz (THz) imaging ranging from 0.1 to 10 THz has received increasing attention in the fields of security screening, aerial imaging, medical diagnostics and non-destructive testing [1, 2]
All results are provided for signal-tonoise ratio (SNR) of 20dB to ensure a realistic channel response in the presence of additional loss factors
In this paper, a CS-based method compatible with Fourierbased techniques for NF mm-wave imaging was presented in a practical multiple-input multiple-output (MIMO) scenario
Summary
Active terahertz (THz) imaging ranging from 0.1 to 10 THz has received increasing attention in the fields of security screening, aerial imaging, medical diagnostics and non-destructive testing [1, 2]. Visible and infrared frequencies can provide very high resolution, they cannot penetrate through some materials such as clothing. For applications such as security screening, THz frequencies are ideal and can be used to detect hidden objects under clothing. These waves provide a resolution commensurate with the size of the aperture [4]. Fourier-based reconstruction techniques offer significant potential due to high computational efficiencies. Such techniques suffer from several limitations, such as uniform sampling requirement, typically achieved at the Nyquist limit
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