Indoor Human Motion Recognition Based on FMCW Radar and Threshold Comparison Algorithm

Radar technology, particularly frequency-modulated continuous wave (FMCW) radar, has garnered attention in the field of smart home monitoring owing to its high sensitivity, long-range surveillance capabilities, and privacy-preserving characteristics. This study proposed a human motion state recognition system to recognize motion states based on the spectra from radar signals in a home environment. The velocity of a target is assessed by comparing a micro-Doppler signature against a velocity threshold, and its height signature discerns between high and low postures against a height threshold. The horizontal position of the target is determined using a range–angle map. The proposed threshold algorithm defines the motion state using the velocity, height postures and indoor position. Subsequently, the performance of the system is evaluated by conducting experiments on 10 subjects. The results demonstrate the efficacy of the proposed method, achieving an accuracy of approximately 85%. In continuous-action experiments involving sequences of movements, the system achieved recognition accuracy exceeding 90%.