TITLE

An MEF-Based Localization Algorithm against Outliers in Wireless Sensor Networks

AUTHOR(S)
Dandan Wang; Jiangwen Wan; Meimei Wang; Qiang Zhang
PUB. DATE
July 2016
SOURCE
Sensors (14248220);Jul2016, Vol. 16 Issue 7, p1041
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Precise localization has attracted considerable interest inWireless Sensor Networks (WSNs) localization systems. Due to the internal or external disturbance, the existence of the outliers, including both the distance outliers and the anchor outliers, severely decreases the localization accuracy. In order to eliminate both kinds of outliers simultaneously, an outlier detection method is proposed based on the maximum entropy principle and fuzzy set theory. Since not all the outliers can be detected in the detection process, the Maximum Entropy Function (MEF) method is utilized to tolerate the errors and calculate the optimal estimated locations of unknown nodes. Simulation results demonstrate that the proposed localization method remains stable while the outliers vary. Moreover, the localization accuracy is highly improved by wisely rejecting outliers.
ACCESSION #
120515006

 

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