  Radio frequency sensor networks are becoming increasingly popular as an
indoor localization and monitoring technology for gaining unobtrusive
situational awareness of the surrounding environment. The localization effort
in these networks is built upon the well-established fact that the received
signal strength measurements vary due to a person's presence on the
line-of-sight of a transmitter-receiver pair. To date, modeling this decrease
in received signal strength and utilizing it for localization purposes have
received a considerable amount of attention in the research field. However,
when the person is in the close vicinity of the line-of-sight but not
obstructing it, the signal reflected from the human body is also affecting the
received signal strength and can be used for occupancy assessment purposes. In
this paper, we first model the effect of human-induced reflections as a
function of communication frequency, and then use the model as a basis for
energy based occupancy detection. The derived methods are evaluated numerically
and the detection probability of the proposed detector is validated with
experimental data. The results suggest that when more than eight frequency
channels are utilized, presence of a person can be detected using RSS
measurements of a single transmit-receive pair with detection probability
higher than 0.95 and false alarm probability less than 0.01 in an area of 2 m x
2.5 m. Moreover, the important implications of the studied methods on the
available narrowband radio frequency sensor network applications are discussed
in detail.
