FFT-based 220 GHz Sparse Imaging for Target Detection

Abstract

This paper introduces two fast imaging algorithms based on Fast Fourier Transform (FFT) for 220 GHz synthetic aperture imaging application of target detection with multi-static multiple-input and multiple-output (MIMO) array-FFT/IFFT approach and FFT matched filtering. Zero padding is proposed to improve the image quality when large sampling space is used. In addition, multi-pass synthetic aperture imaging is proposed to achieve higher image quality without increasing system cost. The 6 mm resolution at 1.4 m is achieved and reconstruction time of 200 mm × 200 mm is as less as 0.2 s. And proposed sparse imaging with low rank matrix recovery (LRMR) technique is potential to further save system cost without comprise on high image quality.

Fast image reconstruction for near-field terahertz imaging with multistatic non-uniform sparse arrays

“…Fourier-based image reconstruction techniques [18,28]. In [28], the effect of this gap on the final results is shown, and to neutralize it, an additional phase interpolation step in the virtual array center is presented.…”

“…Using some types of multiple-input multiple-output (MIMO) arrays is a suitable option to reduce the number of elements [14][15][16]. In particular, sparse periodic arrays (SPAs) with large inter-element spacing have recently been proposed for multistatic MIMO THz imaging systems [16][17][18]. However, the special multistatic structure of SPA is such that it is not possible to directly apply conventional fast Fourier transform (FT)-based image reconstruction techniques in the nearfield (NF) [19,20].…”