Abstract
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 (mobile phones, PDA). Three positioning algorithms were considered: minimal Euclidian distance, intersections of RSSI-Isolines and a stochastic model based on Bayes' theorem. Two measuring testbeds, a museum's exhibition room and an empty seminar room, four different types of PDA (Dell, Fujitsu, HP, T-Mobile) and two types of access points (Netgear, Lancom) were used. Results show that positioning can be achieved with an average accuracy of approx. 2-3 metres. WLAN capable mobile devices behave differently in receiving RSSI values of a base station. For reasons of standardization a linear correlation between different receiving levels of PDA was investigated.
Highlights
Location based services (LBS) will be one of the most exiting features of the generation wireless systems
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
Three positioning algorithms were considered: minimal Euclidian distance, intersections of RSSI-Isolines and a stochastic model based on Bayes' theorem
Summary
Location based services (LBS) will be one of the most exiting features of the generation wireless systems. Location based services are already established in the area of mobile phone networks using the global positioning system (GPS) as outdoor positioning component. Since GPS is not working indoors, establishing LBS within buildings needs an indoor wireless network, for instance WLAN, together with an positioning system [1]. The aim of the activities presented in this paper was the investigation of different WLAN positioning algorithms for indoor position based applications. The increase of existing WLAN infrastructures inside of buildings and the commercial availability of WLAN capable mobile devices leads to the question, whether an indoor positioning using such infrastructures and devices would be accurate enough for mobile indoor applications. Several mathematical methods exist for calculating the current position. We investigated the accuracy of determining the current position using three different algorithms
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