부산대학교 도서관

Non-contact vital sign detection using radar mounted on a flying platform is relevant for many applications especially for search and rescue operations in post-disaster situations. However, the vital sign is weak and easily covered by the noise and clutter. In addition, a small random movement from radar and/or humans will negatively affect detection accuracy. Thus, to address this problem, this paper proposes the detection and extraction technique of vital signs of nonstationary humans by applying sequential processing employing adaptive thresholding, image processing, and principal component analysis. The proposed method aims to be applied in detecting life signs using radar on a hovering drone. To imitate this scheme, in this study, the targeted human moves back and forth randomly in front of the radar. The results obtained by millimeter-wave radar demonstrate the ability of the proposed method to detect human respiration signs.