Paper Info
Title
An Improved RFID-Based Locating Algorithm by Eliminating Diversity of Active Tags for Indoor Environment
Abstract
The location awareness is a crucial foundation for perceptions of the surroundings in the smart environment. Radio frequency identification (RFID), as one of the most promising technologies, plays a more important role in the indoor location awareness. This paper surveys current RFID-based locating research and discusses the problem that is brought by the tag's diversity derived from different manufacturer types and different used-time of built-in battery. We present the algorithm named RFDiffFreeLoc to improve the location precision by eliminating the dissimilarity among tags. In the stimulation experiments, we analyze the impact of noise on performance and contrast our algorithm with the existing LANDMARC algorithm. The simulation performances show that our algorithm is feasible via two metrics: the mean error and cumulative error distribution. The results indicate that RFDiffFreeLoc significantly increases the locating accuracy: when the space between the reference tags is 1 m, the mean error drops 0.076–0.344 m according to various noise conditions. Furthermore, a prototype system named RFHome is deployed for validating the algorithm in the actual home environment. The practical experimental results demonstrate that our algorithm is more effective than previous LANDMARC algorithm.
Year
DOI
Venue
2009
10.1093/comjnl/bxn039
Comput. J.
Keywords
Field
DocType
improved rfid-based locating algorithm,mean error drop,location awareness,existing landmarc algorithm,actual home environment,previous landmarc algorithm,indoor location awareness,indoor environment,mean error,cumulative error distribution,active tags,different manufacturer type,location precision
Smart environment,Computer science,Mean squared error,Algorithm,Radio-frequency identification,Location awareness
Journal
Volume
Issue
ISSN
52
8
0010-4620
Citations 
PageRank 
References 
5
0.46
5
Authors
5
Name
Order
Citations
PageRank
Ting Zhang150.46
Zhenyong Chen231215.30
Yuanxin Ouyang312121.57
Jiuyue Hao4181.63
Zhang Xiong51069102.45