Bayesian filtering for a bluetooth positioning system

Abstract

Positioning systems are one of the multiple applications of the wireless sensor networks. These networks are very adequate in environments where other positioning technologies, as satellite systems, do not work. Bluetooth is a promising technology, since it is present in any kind of portable devices. By using the received signal strength indicator (RSSI) it is possible to make an estimation of the distance between a transmitter and a receiver. By using this information, it is possible to develop an algorithm that estimates positions, even with the bluetooth constraints when the RSSI is obtained. Our experimental results show that our algorithm, based on a particle filter, can achieve a good performance.