Wi-Fi-Based Posture Imaging Radar for Vital Sign Monitoring and Fall Detection

This article presents an advanced radar system that utilizes common Wi-Fi signals for human imaging and Doppler detection. The system employs a time-division multiplexing (TDM) multiple-input-multiple-output (MIMO) radar configuration, synchronizing a local oscillator with the transmitted Wi-Fi signal through injection locking to detect Doppler phase shifts in the returning Wi-Fi echoes. A significant challenge in human imaging is the varying radar cross sections (RCSs) between the torso and limbs, which can obscure limb images. To address this issue, this system incorporates a dc nulling filter in its digital signal processor as an RCS equalizer. This filter enhances rapidly moving limb images, while maintaining the clarity of quasi-stationary torso images. The experimental results reveal that the system produces high-resolution images that distinctly depict limbs, facilitating the recognition of human postures and activities. Additionally, it effectively captures posture images in various scenarios, including standing, sitting, falling, and lying down. These captured images are essential for both vital sign monitoring and fall detection.