A Non-line-of-Sight Localization Method Based on the Algorithm Residual Error Minimization

Author(s):  
Sunan Li ◽  
Jingyu Hua ◽  
Feng Li ◽  
Fangni Chen ◽  
Jiamin Li
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Yan Wang ◽  
Xuehan Wu ◽  
Long Cheng

The localization technology is the essential requirement of constructing a smart building and smart city. It is one of the most important technologies for wireless sensor networks (WSNs). However, when WSNs are deployed in harsh indoor environments, obstacles can result in non-line-of-sight (NLOS) propagation. In addition, NLOS propagation can seriously reduce localization accuracy. In this paper, we propose a NLOS localization method based on residual analysis to reduce the influence of NLOS error. The time of arrival (TOA) measurement model is used to estimate the distance. Then, the NLOS measurement is identified through the residual analysis method. Finally, this paper uses the LOS measurements to establish the localization objective function and proposes the particle swarm optimization with a constriction factor (PSO-C) method to compute the position of an unknown node. Simulation results show that the proposed method not only effectively identifies the LOS/NLOS propagation condition but also reduces the influence of NLOS error.


Author(s):  
Alireza Safaie ◽  
Reza Shahbazian ◽  
Seyed Ali Ghorashi

<p>Target localization is an important issue for many applications in wireless sensor networks. However, it is rather difficult to maintain the localization accuracy in mixed line-of-sight (LOS) and non-line-of-sight (NLOS) environments as NLOS propagation leads to larger error than what LOS does. In this paper, we propose a new target localization method in mixed environments where NLOS is dominant and only one base node might be in LOS toward target. We use the cooperation between receiver nodes and the direction of arrival (DOA) of received signals to estimate the target’s location. The proposed cooperative target localization method tries to identify a base node that has LOS with respect to target node and use the LOS information for precise positioning of target node. We simulate the proposed method to analyze its performance. Simulation results confirm that our proposed method improves the localization accuracy on average by 20 percent in comparison with traditional cooperative methods.</p>


2007 ◽  
Author(s):  
Jonathon Emis ◽  
Bryan Huang ◽  
Timothy Jones ◽  
Mei Li ◽  
Don Tumbocon

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