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

被引：7

作者：

Wang, Dandan ^{[1
]}

Wan, Jiangwen ^{[1
]}

Wang, Meimei ^{[1
]}

Zhang, Qiang ^{[1
]}

机构：

[1] Beihang Univ, Sch Instrumentat Sci & Optoelect Engn, Xueyuan Rd 37, Beijing 100191, Peoples R China

来源：

SENSORS | 2016年 / 16卷 / 07期

基金：

中国国家自然科学基金;

关键词：

wireless sensor networks; localization; outliers; maximum entropy principle; fuzzy set theory; RANGE-FREE LOCALIZATION; SECURE LOCALIZATION;

D O I：

10.3390/s16071041

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

Precise localization has attracted considerable interest in Wireless 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.

引用

页数：14

共 27 条

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