Spatial interpolation of Wi-Fi RSS fingerprints using model-based universal kriging

Wi-Fi RSS Fingerprint based navigation has enjoyed increasing popularity as a solution for indoor navigation in the last decade. Recently, methods for interpolation of Wi-Fi databases have become the focus of research. This paper shows how common models for Wi-Fi signal propagation can be included into the interpolation method by using universal Kriging, a method that relies on mixed model containing both spatially stochastic and deterministic components. It is shown that, theoretically, it can achieve a very precise reproduction of the spatial distribution of Wi-Fi RSS. The major remaining challenge of this method, however, is to find a suitable representation of the spatial depedency in the variogram, which cannot be estimated properly from recorded Wi-Fi signals. Both the high potential and this vulnerability are highlighted using simulation and measurement results.