WLAN Indoor Tracking Method via Improved Particle Filter Algorithm

Author

Xu, Yubin ; Liu, Jingyu ; Ma, Lin ; Peng, Lang

Author_Institution

Commun. Res. Center, Harbin Inst. of Technol., Harbin, China

fYear

2010

fDate

17-19 Sept. 2010

Firstpage

1078

Lastpage

1082

Abstract

WLAN Indoor tracking system is presented based on the comparison between the off-line pre-stored Radio-map and new recorded signal strength in the on-line phase to estimate user´s motion trajectory. Furthermore, the improved particle filter tracking algorithm that consists of the particles-reference points (P-RPs) transferring for getting the likelihood function and velocity estimation from the ANN positioning results is also discussed in this paper. And also, the experiment shows that this improved particle filter tracking algorithm achieves great accuracy performance in tracking trajectory aspect without any velocity-measurement hardware. Finally, the feasibility and effectiveness of this improved WLAN indoor particle filter tracking algorithm are verified without velocity-measurement hardware.

Keywords

neural nets; particle filtering (numerical methods); wireless LAN; WLAN indoor tracking method; artificial neural network positioning; improved particle filter algorithm; likelihood function; off-line prestored radio map; particles reference points; recorded signal strength; tracking trajectory aspect; user motion trajectory; velocity estimation; Artificial neural networks; Estimation; Legged locomotion; Particle filters; Radar tracking; Trajectory; Wireless LAN; P-RPs; WLAN; particle filter; tracking; velocity estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Pervasive Computing Signal Processing and Applications (PCSPA), 2010 First International Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4244-8043-2

Electronic_ISBN

978-0-7695-4180-8

Type

conf

DOI

10.1109/PCSPA.2010.265

Filename

5635697