In this work we present RAPID, a joint communication and radar (JCR) system
based on next-generation IEEE 802.11ay WiFi networks operating in the 60 GHz
band. In contrast to most existing approaches for human sensing at
millimeter-waves, which employ special-purpose radars to retrieve the
small-scale Doppler effect (micro-Doppler) caused by human motion, RAPID
achieves radar-level sensing accuracy by retrofitting IEEE 802.11ay access
points. For this, it leverages the IEEE 802.11ay beam training mechanism to
accurately localize and track multiple individuals, while the in-packet beam
tracking fields are exploited to extract the desired micro-Doppler signatures
from the time-varying phase of the channel impulse response (CIR). The proposed
approach enables activity recognition and person identification with IEEE
802.11ay wireless networks without requiring modifications to the packet
structure specified by the standard. RAPID is implemented on an IEEE
802.11ay-compatible FPGA platform with phased antenna arrays, which estimates
the CIR from the reflections of transmitted packets. The proposed system is
evaluated on a large dataset of CIR measurements, proving robustness across
different environments and subjects, and outperforming state-of-the-art sub-6
GHz WiFi sensing techniques. Using two access points, RAPID reliably tracks
multiple subjects, reaching activity recognition and person identification
accuracies of 94% and 90%, respectively.Comment: 16 pages, 18 figures, 4 table