Sensors | |
ANLoC: An Anomaly-Aware Node Localization Algorithm for WSNs in Complex Environments | |
Lei Chen1  Pengfei Xu1  Tianhao Cui1  | |
[1] School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; | |
关键词: wireless sensor networks; anomaly-aware node localization; low-rank matrix decomposition; mixture of Gaussians; | |
DOI : 10.3390/s19081912 | |
来源: DOAJ |
【 摘 要 】
Accurate and sufficient node location information is crucial for Wireless Sensor Networks (WSNs) applications. However, the existing range-based localization methods often suffer from incomplete and detorted range measurements. To address this issue, some methods based on low-rank matrix recovery have been proposed, which usually assume noises follow single Gaussian distribution or/and single Laplacian distribution, and thus cannot handle the case with wider noise distributions beyond Gaussian and Laplacian ones. In this paper, a novel Anomaly-aware Node Localization (ANLoC) method is proposed to simultaneously impute missing range measurements and detect node anomaly in complex environments. Specifically, by utilizing inherent low-rank property of Euclidean Distance Matrix (EDM), we formulate range measurements imputation problem as a Robust
【 授权许可】
Unknown