An Identity Perception Algorithm Based on WiFi Channel State Information

Gait recognition is an important biometric technology, and also an important research direction in the field of human-computer interaction. Since the gait information provided by each person's walking is different, different people can be identified according to different gait information. Based on WiFi CSI analysis, we propose another gait recognition model Wi-IP (WiFi-Identity Perception), which achieves good results with a small number of training samples. In the corridor environment, we conducted a lot of experiments to ensure the accuracy of identity recognition. In the system model we designed, when each group of 2 to 6 volunteers walked 3.5 meters, the average recognition accuracy of our system was between 82.5% and 100%.