RSSI based WLAN Indoor Positioning with Personal Digital Assistants

Often mobile devices like mobile phones or personal digital assistants (PDA) are equipped with IEEE 802.11 WLAN adapters. Furthermore, within many buildings a WLAN infrastructure is available. The aim of this work is to investigate the quality of different indoor positioning methods based on values of WLAN received signal strength index (RSSI) using commercially available devices (smart phones, personal digital assistants). Three positioning algorithms were considered: minimal Euclidian distance, intersections of RSSI-isolines and a stochastic model based on Bayes' theorem. A measuring test bed within an empty seminar room, four different types of personal digital assistants (Dell, Fujitsu, HP, T-Mobile) and two types of access points (Netgear, Lancom) were used. No modification of hardware and software was conducted.