Low Complexity Algorithm for Range-Point Migration-Based Human Body Imaging for Multistatic UWB Radars

摘要

High-resolution, short-range sensors that can be applied in optically challenging environments (e.g., in the presence of clouds, fog, and/or dark smog) are in high demand for various applications. Ultrawideband radar is a promising sensor that is suitable for short-range surveillance or watching sensors. Range-point migration (RPM) has been recently established as a promising imaging approach to achieve accurate and real-time 3-D imaging. However, when objects with many scattering points are dealt with, such as a human body, RPM suffers from high computational costs. In this letter, we propose an algorithm with a lower complexity for an RPM-based 3-D imaging method by introducing a sampling-based scattering center extraction with a simplified evaluation function, in which an efficient sample pattern is provided by a golden ratio. The results from a finite-difference time-domain-based numerical test, which introduces a realistic human body object, demonstrate that our proposed method remarkably reduces the computational cost without sacrificing the reconstruction accuracy.