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

作者：Wang, Dandan; Wan, Jiangwen^*; Wang, Meimei; Zhang, Qiang

来源：Sensors (Switzerland), 2016, 16(7): 1041.

DOI：10.3390/s16071041

• wireless sensor networks
• localization
• outliers
• maximum entropy principle
• fuzzy set theory

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 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.

• 出版日期2016-7
• 单位北京航空航天大学