About this Journal Submit a Manuscript Table of Contents
International Journal of Distributed Sensor Networks
Volume 2013 (2013), Article ID 247306, 7 pages
Research Article

Indoor Pedestrian Positioning Tracking Algorithm with Sparse Anchor Nodes

School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China

Received 7 June 2013; Accepted 28 June 2013

Academic Editor: Shuai Li

Copyright © 2013 Zhou Yong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In order to solve the indoor pedestrian positioning and tracking problems under the condition of sparse anchor nodes, this paper presents a new tracking scheme which predicts the staff position under the condition of indoor location fingerprints based on particle filter. In the proposed algorithm, the indoor topology is adopted to constrain and correct the results. Simulation results show that the proposed algorithm can significantly improve the accuracy of indoor pedestrian positioning and tracking more than the Kalman filter and k-nearest neighbor (KNN) algorithms. The simulation results also show that under the condition of sparse nodes deployment good tracking results can still be achieved through the adoption of indoor topology and the average positioning error is about 1.9 m.