A Novel WiFi-Based Temporal Precision Detection System With Enhanced CSI Sampling

Integrated sensing and communication (ISAC) has emerged as a prominent research focus in the domains of 5G-Advanced (5G-A), 6G, and wireless fidelity (WiFi). As a passive sensing technology, WiFi-based human detection has garnered widespread attention due to its privacy, unobtrusiveness, and convenience in practical applications. This letter introduces a WiFi-based human intrusion detection system utilizing channel state information (CSI). By refining the CSI phase sampling points through the proposed sequence particle filter (SPF) CSI sampling method, the system reduces the amount of data needed for real-time sensing. A comprehensive preprocessing procedure is presented to filter out noise interference and mitigate channel fading during CSI collection. The proposed human intrusion detection algorithm accurately identifies fluctuations in the CSI phase time series, thereby determining the presence of a human and the exact moments of intrusion.