Accurate Indoor localization with Channel State Information

Device-free localization(DFL) is an emerging technology to detect whether there exists any target(s) in the area of interests without carrying any device to them. It is an essential primitive for a large-scale range of application including intrusion localization of warehouse, elder care at home, and action about hostage rescue, etc. Most DFL relying on received signal strength (RSS) have proposed to be able to provide acceptable accuracy and distance error. Although RSS can be easily measured with commercial equipments, it is suspectable to measurement itself due to multipath effect in indoor environment. In this paper, we present the Ailot approach to overcome the preceding RSS-based limitation. Ailot explores properties of Channel State Information(CSI) from PHY layer and uses the novel feature extracted from CSI to leverages frequency and spatial diversity. The target localization of Ailot approach is conducted with maximum likelihood method. We implement Ailot approach with commercial IEEE 802.11n NICs and evaluate its performance in a real-world indoor environment. Experimental results show that Ailot can achieve high localization accuracy and distance error. Moreover, comparing to RSS-based scheme, our CSI-based approach enables better localization performance in accuracy and distance error.