Refining Wi-fi Based Indoor Positioning

The increasing demand for location-based services inside buildings has made indoor positioning a significant research topic. This study deals with indoor positioning using the Wireless Ethernet IEEE 802.11 (Wi-Fi) standard that has a distinct advantage of low cost over other indoor wireless technologies. Most of the proposed Wi-Fi indoor positioning systems use either proximity detection via radio signal propagation models or location fingerprinting techniques, the latter being usually more accurate. The aim of this study is to examine several aspects of Wi-Fi location fingerprinting based indoor positioning that could enhance the positioning accuracy, without demanding a larger radio map with additional signal strength measurements in more locations, namely making use of weakly-sensed access points, making use of the different available Wi-Fi frequency bands, using device’s orientation information provided by a built-in digital compass, and augmenting the radio map using Locally Weighted Regression.