부산대학교 도서관

With the rapid development of the aging population, radar-based fall detection has become a research hotspot in the field of health monitoring. In this paper, a fall detection method based on the human motion scattering model is proposed to enhance the accuracy of fall detection and address the issue of challenging data acquisition. Specifically, the kinematics model of the human body is described, and the radar backscattering model under human motion is established. Simulation research and analysis of human micro-Doppler characteristics are conducted to analyze the correlation between the characteristic micro-Doppler information and body parts when the human body is walking and falling. This analysis aims to simplify the backscattering model of human radar and enhance detection efficiency. The experimental results demonstrate that the method effectively reduces the probability of false alarm and missing alarm.