FFT-Based 220 GHz Sparse Imaging for Target Detection

Abstract

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