An Indoor Position Tracking Technique based on Data Fusion for Ambient Assisted Living

Accurate indoor position tracking of moving users is essential in ambient assisted living (AAL) applications. In this paper, in view of designing a smart rollator helping impaired or elderly people to navigate in indoor environments (e.g. shopping malls, railway stations or airports), a position tracking estimation technique is described and the performance of different variants are compared through simulations. The proposed solution is based on an extended Kalman filter (EKF), which in turn relies on the measurement data provided by two encoders, a gyroscope a short-range radio-frequency identification (REID) system and a possible further low-rate, high-accuracy orientation measurement system. Some simulation results confirm that the position tracking accuracy of the proposed technique is fairly good even if the distance between REID tags is quite large (i.e. in the order of a few meters).