The indoor positioning technique based on neural networks

This paper presents an indoor positioning technique based on neural networks (NN). The received signal strengths (RSS) sensed by Zigbee wireless sensor network were used to estimate the position of object. From the simulation results shown, the NN technique proposed still has the high accuracy even the signal strengths sensed are unstable. Besides, from the experimental results shown, it is concluded that the positioning accuracy could be improved if the number of wireless sensors is added more. In this research, the polar coordinate system of object´s position was also studied. It is found that the accuracy of positioning by polar form is better than by rectangular form.