Advanced THz MIMO Sparse Imaging Scheme Using Multipass Synthetic Aperture Focusing and Low-Rank Matrix Completion Techniques

This article proposes an advanced THz multiple-input-multiple-output (MIMO) near-field sparse imaging scheme for target detection that uses single-pass synthetic aperture focusing and multipass interferometric synthetic aperture focusing techniques to improve imaging effectiveness and efficiency. It benefits from the MIMO of the linear sparse periodic array (SPA) and random undersampling sparse imaging to reduce sampling data and system cost. Both simulated and proof-of-concept experimental results have verified the scheme, revealing that the single-pass synthetic aperture imaging approach is sufficient to identify pure metallic targets with 3.87% of
$\lambda /2$
sampling data. The multipass interferometric synthetic aperture imaging approach is capable of improving image quality on the image signal-to-noise ratio (SNR) and contrast, which is ideal for detecting more challenging targets. The random sparse imaging with help of the low-rank matrix completion (LRMC) technique has shown the promising potential of achieving equivalent image quality when further reducing 43.75% data in the experiment of five-pass imaging on a complex target; this corresponds to 82.51% data reduction compared to
$\lambda /2$
sampling.