A SAR Imaging Method for Walking Human Based on mωka-FrFT-mmGLRT

Abstract

Synthetic aperture radar (SAR) human-imaging technology has been widely used in the fields of security screening and activity recognition. However, most of the existing methods aim at stationary human targets, resulting in severe restrictions on their potential applications. In this article, an SAR imaging method for walking human is proposed with short aperture terahertz (THz) radar. This method is based on a modified wavenumber domain approximate algorithm ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}{\omega }$ </tex-math></inline-formula> ka), whose interpolation mapping is modified according to the approximation of region of interest (RoI). Because the nonrigid motion phase error caused by the walking human would lead to severe deformation and blur in imaging results, a compensation processing is essential. To figure it out, the fractional Fourier transform combined with the maximum and minimum generalized likelihood ratio test (FrFT-mmGLRT) is devised in this article. Within a short aperture time, the nonrigid motion of walking human can be approximately assumed as a superposition of the rigid movements of different human body parts. Particularly, by taking advantage of the superposition property of FrFT, the motion phase errors of different human body parts are distinguished and estimated by jointly searching for the peaks of FrFT energy spectrum. Furthermore, the mmGLRT-based composite imaging technique is utilized to obtain a whole body result from the compensated results of different body parts. Finally, numerical simulation and real experiments are conducted to verify the feasibility and capability of the proposed method for walking human SAR imaging.