Bayesian filters for ToF and RSS measurements for indoor positioning of a mobile object

The article describes three different types of Bayesian filtering methods (Kalman filter, particle filter, and grid-based filter) applied for indoor localization in NanoLOC (IEEE 802.15.4a) wireless sensors network. Received Signal Strength, Time-of-flight measurements and the building structure were used for position calculations. The comparison of the applied algorithms revealed conditions at which one algorithm is superior to others. The techniques described in this paper are not depending on the used RF technology.