Title :
Data Fusion of the Real Time Positioning System Based on RSSI and TOF
Author :
Zhe Dong ; Yao Wu ; Dehui Sun
Author_Institution :
Beijing Key Lab. of Fieldbus Technol. & Autom., North China Univ. of Technol., Beijing, China
Abstract :
In this paper, the data fusion algorithm for position estimation of the wireless sensor networks is investigated. A hybrid position scheme with both radio Based ranging measurement and time-Based ranging measurement is proposed. The position estimation performances of RSSI and TOF are compared and analyzed. A novel data fusion algorithm along with traditional Kalman filter is advanced to improve the positioning and tracking accuracy. Several simulation experiments are carried out, which show the validity of the presented algorithm.
Keywords :
Kalman filters; indoor radio; position measurement; sensor fusion; wireless sensor networks; RSSI; TOF; data fusion; hybrid position scheme; position estimation; radio based ranging measurement; real time positioning system; time based ranging measurement; traditional Kalman filter; wireless sensor networks; Accuracy; Distance measurement; Mobile nodes; Neural networks; Noise; Training; RSSI; TOF; data fusion; indoor-location; neural networks;
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-0-7695-5011-4
DOI :
10.1109/IHMSC.2013.267
