TAIL: Two-level approach for indoor localization

Popularity of ubiquitous computing increases the importance of location-aware applications, which increases the need for finding location of the user. In this paper, we present a novel localization method for indoor environments using Wi-Fi infrastructure. While localization using Wi-Fi is cost effective, handling the obstructions which are the main cause of signal propagation error in indoor environments is a challenging task. We address this problem in two levels, resulting in increased accuracy of localization. In the first level, we "localize" the residing area of user node in coarse granularity. Then, we use building layout to find the objects that attenuate the signal between the reference node and the coarse estimate of the location of user node. Using multi-wall propagation model, we apply corrections for all obstructions and find the location of user node. Empirical results based on experiments conducted in lab-scale, shows meter-level accuracy. © 2007 International Federation for Information Processing.