Abstract
The vast market of location-based services (LBSs) has brought opportunities for the rapid development of indoor positioning technology. In current indoor venues, by considering the fact that the wireless local area network (WLAN) infrastructure is widely deployed, the indoor WLAN localization method has become the focus of study. Nowadays, the WLAN module is used widely in a large number of advanced mobile devices, and meanwhile there are a variety of WLAN mobile access points (APs) in indoor environment. In this circumstance, due to the uncertainty of the state of mobile APs, the associated received signal strength (RSS) data are usually lowly dependent on the locations, which will consequently result in the decrease in localization accuracy. To solve this problem, a new method of mobile AP detection based on the density-based spatial clustering of applications with noise (DBSCAN) is proposed. This method aims to identify mobile APs in target area so as to eliminate the adverse impact of mobile APs on localization accuracy.
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