Open AccessA Propagation Condition Identification and Non-Line of Sight Error Mitigation Algorithm in Wireless Sensor Network
Author(s) -
Hao Chen,
Siyi Lian,
Hao Yang,
Rongguang Wu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1453/1/012046
Subject(s) - non line of sight propagation , computer science , kalman filter , identification (biology) , algorithm , wireless sensor network , fuse (electrical) , wireless , line (geometry) , false alarm , node (physics) , real time computing , artificial intelligence , computer network , mathematics , telecommunications , engineering , botany , geometry , structural engineering , electrical engineering , biology
Node localization is one of key technologies in wireless sensor networks (WSN). In practice, the occlusion of obstacles often leads to large non-line-of-sight (NLOS) error. Therefore, the misidentification of LOS (line-of-sight)/NLOS conditions can seriously reduce the accuracy of localization algorithms in WSN. In this paper, we propose a novel localization algorithm based on hypothesis testing method, which combines the NLOS condition identification algorithm and the extended Kalman filter method to mitigate the NLOS error. Moreover, we introduce the false alarm rate fa to fuse the estimated values in the LOS/NLOS condition to obtain more accurate results. The simulations demonstrate that the proposed algorithm can effectively reduce the influence of NLOS error and improve the localization accuracy.