Practical Considerations For RSS RF Fingerprinting Based Indoor Localization Systems

Abstract

There are different location estimation approaches in order to determine the position of a mobile users precisely in indoor environments. In this study, in order to determine the position of the mobile user at the shopping malls received signal strength (RSS) RF fingerprint based approaches is considered. Wi-Fi and GSM RSS data has been collected by using LG Nexus 4 cell phone at Gebze Center shopping mall in Gebze, Kocaeli. By using the collected data, the effects of different machine learning algorithms, number of training data, number of measurement grid, and signal type on the performance of the localization systems are studied. According to the results, it is observed that, combining Wi-Fi and GSM RSS data measurements decreases the location estimation error.