“Statistical Modelling based probabilistic method for Position estimation in Indoor Environment”

Location information is of paramount importance in context aware Ambient Intelligence (AmI), Smart Space, traffic monitoring, surveillance network and cooperative communications services. This paper describes a Positioning determination solution based on wireless local area network (WLAN) signals. Position determination is based on the statistical modeling of the received signal at any position. This paper presents a probabilistic based statistical modeling approach for location estimation which incorporates fusion strategy in final step to combine efficiently the location individually reported by each WLAN transmitter. The system builds a radio map of the environment. The presented system is easier to implement and provide sufficiently good performance under all conditions. The accuracy with the 90% probability is reported to be 1.85 meters where as average error is reported to be 2.1 meters.