Efficient Radio Map Update Algorithm for Indoor Localization

The GPS, location-based services and navigation systems are well known terms in the case of outdoor environment. In the recent years the location-based services in indoor environment are gaining more attention as well. Since there is no GPS like, widely available technology for indoor localization, several methods were developed in the past. One of the very popular method is using some existing radio infrastructure like Wi-Fi inside a building and creating the signal strength map of those radio transmitters. Since the field strength is location dependent for each radio station, measuring the RSSI value the location of the receiver can be estimated. However, collecting and maintaining time-to-time a relatively large field strength database is a challenging task. To ease this work and increase the overall performance of such a localization system we investigate the motion classification and floorplan constrains algorithm effectiveness to update the field strength map. The overall performance of the localization system is evaluated in the terms of the maintenance of the fingerprint database using real life localization scenarios.