NLoS Mitigation in ToA Localization Based on Spatial Correlation Filter and Iterative Minimum Residual

查看全文 作　　者：Luo Haiyong Liu Shujing Liu [1]Xiaoming

机构地区：[1]Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100191, P. R. China

出　　处：《China Communications》索引2012年第9卷第4期,共7页

基　　金：supported by the National Natural Science Foundation of China under Grants No.60973110,No.61003307;the Natural Science Foundation of Beijing City of China under Grant No.4102059;the Major Projects of Ministry of Industry and Information Technology under Grants No.2010ZX03006-002-03,No.2011ZX03005-005 摘　　要：To mitigate the Non-Line-of-Sight (NLoS) error which seriously affects the localization accuracy and robustness in complex indoor environment,a novel Iterative Minimum Residual (IMR) based on the consistency hypothesis of the residual and the error is proposed in this paper.It chooses the best subset of measurements to calculate the coordinates of the unknown node by comparing the residuals obtained with different subsets of beacons.To reduce the time complexity of the IMR algorithm,Spatial Correlation Filter (SCF) is also proposed,which can remove the most serious NLoS distance with low calculation cost.Combined with the proposed SCF and IMR algorithm,nodes can be localized with high accuracy and low time complexity.Experimental results with real dataset demonstrate that the proposed algorithm can identify the NLoS range effectively with about 50% time cost of employing SCF only. 关键词：空间相关性 NLOS 过滤器剩余迭代本地化 TOA 时间复杂度

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NLoS Mitigation in ToA Localization Based on Spatial Correlation Filter and Iterative Minimum Residual

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