Fast Processing Approach for Near-Field Terahertz Imaging with Linear Sparse Periodic Array

Abstract

The benefits of terahertz (THz) radiation have increased its use, especially in imaging systems. Recently, the use of a linear sparse periodic array (SPA) has been proposed as an effective solution for two-dimensional (2D) scanning in THz imaging systems. However, the special multistatic structure of the SPA is such that it is not possible to apply fast Fourier transform-based techniques directly in the near-field (NF). Therefore, in this paper, a fast processing approach based on two Fourier techniques compatible with linear SPA is presented for NF THz imaging. In this approach, we first employ a multistatic-to-monostatic conversion to reduce phase errors due to NF multistatic imaging. Then, to improve the quality of the results, we mathematically derive an interpolation formula to counteract the non-uniform spacing of the virtual array. The modified data is then processed by three rapid techniques (fast Fourier transform (FFT)-inverse fast Fourier transform, matched filtering and a novel 1D FFT-based technique with low computational complexity) to obtain reconstructed images of the scene. Numerical and experimental results confirm the satisfactory performance of the proposed approach in terms of both the computational time and the quality of the reconstructed images.