Wireless local area network (WLAN) technologies are utilized for sensing, which rely on changes in wireless signals in a sensing environment. A number of studies have dealt with channel state information (CSI)-based sensing technologies, although their applications are difficult in an outdoor environment owing to the limited influence of a sensing target object on radio signals. In this paper, we present an outdoor device-free human localization method using IEEE 802.11ac CSI. The key idea is to employ multiple transmitter–receiver pairs to derive sufficient information for human localization. We install multiple WLAN transmitter–receiver pairs to cover an entire localization target area and enable communication between transmitter–receiver pairs to collect CSI data from each pair. We then extract essential CSI components for localization to realize outdoor CSI sensing. A supervised learning method is used to estimate the location of a human. We conducted experiments to collect CSI data using actual WLAN devices in outdoor environments. The experimental evaluations revealed that our system estimated the location of a human in a target area with high accuracies of 93.51 and 92.65% in line-of-sight (LOS) and non-line-of-sight (NLOS) environments, respectively.
All Science Journal Classification (ASJC) codes
- Materials Science(all)