Title :
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
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;
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
DOI :
10.1109/PCSPA.2010.265
