A RSS based indoor tracking algorithm using particle filters

In recent years, the location finger printing techniques draws more attention for the indoor location systems because of the easiness for deployment. The Kalman filter is also applied for indoor tracking system using the location information estimated by location finger printing technique, while the performance would be weak in some more complex indoor environment. In this paper, we develop a new indoor tracking algorithm using received signal strength directly and particle filter is applied for the nonlinear tracking model. The numerical simulation shows the new algorithm outperforms the tracking algorithm using Kalman filter in the former research.