Paper Info
Title
A Localization and Tracking Approach with Sparse Reference Tags
Abstract
In traditional localization systems, it is required that moving object carries a device to transmit or receive signals, and then localization system is able to locate an object based on signal strength it received. In this paper, we propose a new passive localization and tracking approach based on RFID with sparse reference tags, which can estimate the location of moving objects by detecting and analyzing signal strength distribution of target area. We firstly construct a signal fluctuation ellipse model between RFID reader and tag through the experiments, and then present a localization method based on this model. Then a tracking method based on Hidden Markov Model (HMM) is proposed to predict the trajectory of an object in a passive localization system with sparse reference tag. The experimental results show that our method not only reduces the computation complexity and cost but also ensures the accuracy of localization and tracking.
Year
DOI
Venue
2013
10.1109/MSN.2013.80
MSN
Keywords
Field
DocType
sparse reference tags,signal strength distribution,localization method,traditional localization system,rfid reader,localization system,tracking approach,new passive localization,localization systems,hmm,tracking method,signal strength,signal fluctuation ellipse model,localization approach,computational complexity,passive localization,radiofrequency identification,computation complexity,passive localization system,overlapping area,sparse reference tag,rfid tag,hidden markov models,hidden markov model
Pattern recognition,Computer science,Localization system,Signal strength,Artificial intelligence,Ellipse,Hidden Markov model,Computation complexity,Trajectory,Computational complexity theory
Conference
ISBN
Citations 
PageRank 
978-0-7695-5159-3
0
0.34
References 
Authors
7
5
Name
Order
Citations
PageRank
Junhuai Li13916.44
Bo Zhang200.34
Lei Yu342.09
Wang Zhi-xiao43712.28
Hailing Liu5175.09