학술논문

The indoor positioning technique based on neural networks
Document Type
Conference
Source
2011 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) Signal Processing, Communications and Computing (ICSPCC), 2011 IEEE International Conference on. :1-4 Sep, 2011
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Artificial neural networks
Sensors
Wireless sensor networks
Accuracy
Zigbee
Attenuation
Wireless LAN
indoor positioning
neural network
RSS
least-squares estimation
Language
Abstract
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.