The indoor radio propagation channel is typically modeled as a two-state time-variant process, where one of the states represents the channel when the environment is static, whereas the other state characterizes the medium when it is altered by people. In this paper, the aforementioned process is augmented with an additional state. It is shown that the changes in received signal strength are dictated by: 1) electronic noise, when a person is not present in the monitored area; 2) reflection, when a person is moving in the close vicinity of line-of-sight; and 3) shadowing, when a person is obstructing the line-of-sight component of the transmitter-receiver pair. Statistical and spatial models for the three states are derived, and the models are empirically validated. Based on the models, a link line monitoring system is designed, which aims to, first, estimate the temporal state of the channel using a hidden Markov model, and, second, track a person using a particle filter. The results suggest that the presented system outperforms other state-of-The-Art systems in terms of localization accuracy while increasing size of the link's sensing region.
- Device-free localization
- Indoor radio propagation channel
- Received signal strength
- Temporal fading