A hierarchical RSS model for RF-based device-free localization

One common challenge in device-free localization (DFL) with radio frequency sensor networks is that the variations of received signal strength (RSS) become less sensitive to shadow fading and the performance will be degenerated in a cluttered environment. To address this problem, this paper develops a hierarchical model that contributes to refining the description granularity of RSS variations and enhancing the sensitivity of RSS variations to shadow fading. The novelty is twofold. First, the Exponential-Rayleigh model and the diffraction-based model are integrated to form a two degree-of-freedom parametrization that can capture not only the target-induced multipath interferences but also the diffraction fading contributions. Second, the link dependent characterizations of RSS variations are explored by parameterizing the model coefficients in terms of fade level. The proposed model is experimentally validated in the context of radio tomographic imaging (RTI).