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

Volume

2

fYear

2013

fDate

26-27 Aug. 2013

Firstpage

503

Lastpage

506

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on

Conference_Location

Hangzhou

Print_ISBN

978-0-7695-5011-4

Type

conf

DOI

10.1109/IHMSC.2013.267

Filename

6642795