Ricerc@Sapienza

Virtual fingerprints have been proposed in the context of WiFi Fingerprinting Indoor Positioning systems in order to reduce the effort dedicated to offline measurements. In this work, the use of Multi-Wall Multi-Floor indoor propagation models to generate such virtual fingerprints is investigated. A strategy taking into account the impact of user/device orientation on the signal propagation is proposed, leading to the creation of virtual and oriented fingerprints.

Widespread adoption of indoor positioning systems based on WiFi fingerprinting is at present hindered by the large efforts required for measurements collection during the offline phase. Two approaches were recently proposed to address such issue: crowdsourcing and RSS radiomap prediction, based on either interpolation or propagation channel model fitting from a small set of measurements. RSS prediction promises better positioning accuracy when compared to crowdsourcing, but no systematic analysis of the impact of system parameters on positioning accuracy is available.