  Pyroelectric infrared (PIR) sensors are considered to be promising devices
for device-free localization due to its advantages of low cost, less intrusive,
and the immunity from multi-path fading. However, most of the existing
PIR-based localization systems only utilize the binary information of PIR
sensors and therefore require a large number of PIR sensors and a careful
deployment. A few works directly map the raw data of PIR sensors to one's
location using machine learning approaches. However, these approaches require
to collect abundant training data and suffer from environmental change. In this
paper, we propose a PIR-based device-free localization approach based on the
raw data of PIR sensors. The key of this approach is to extract a new type of
location information called as the azimuth change. The extraction of the
azimuth change relies on the physical properties of PIR sensors. Therefore, no
abundant training data are needed and the system is robust to environmental
change. Through experiments, we demonstrated that a device-free localization
system incorporating the information of azimuth change outperforms the
state-of-the-art approaches in terms of higher location accuracy. In addition,
the information of the azimuth change can be easily integrated with other
PIR-based localization systems to improve their localization accuracy.
