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A Triple-Filter NLOS Localization Algorithm Based on Fuzzy C-means for Wireless Sensor Networks by Long Cheng; Yifan Li; Yan Wang; Yangyang Bi; Liang Feng; Mingkun Xue is a Engineering article available to read on EtoBox.

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With the rapid development of communication technology in recent years, Wireless Sensor Network (WSN) has become a promising research project. WSN is widely applied in a number of fields such as military, environmental monitoring, space exploration and so on. The non-line-of-sight (NLOS) localization is one of the most essential techniques for WSN. However, the NLOS propagation of WSN is largely influenced by many factors. Hence, a triple filters mixed Kalman Filter (KF) and Unscented Kalman Filter (UKF) voting algorithm based on Fuzzy-C-Means (FCM) and residual analysis (TF-FCM) has been proposed to cope with this problem. Firstly, an NLOS identification algorithm based on residual analysis is used to identify NLOS errors. Then, an NLOS correction algorithm based on voting and NLOS errors classification algorithm based on FCM are used to process the NLOS measurements. Hard NLOS measurements and soft NLOS measurements are classified by FCM classification. Secondly, KF and UKF are applied to filter two categories of NLOS measurements. Thirdly, maximum likelihood localization (ML) is employed to estimate the position of mobile nodes. The simulation result confirms that the accuracy a

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Author

Long Cheng; Yifan Li; Yan Wang; Yangyang Bi; Liang Feng; Mingkun Xue

Publisher

MDPI AG

Published

2019

Language

EN

Field

Engineering (Physical Sciences)