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Pattern recognition based Kalman filter for indoor localization using TDOA algorithm
Han Tao; Lu Xiaochun; Lan Qi
2010
发表期刊APPLIED MATHEMATICAL MODELLING
ISSN0307-904X
卷号34期号:10页码:2893-2900
摘要In this paper, we will present a motion pattern recognition based Kalman filter (PRKF), and apply it to the time difference of arrival (TDOA) algorithm of indoor localization. The state matrix in Kalman filter (KF) is determined by the motion pattern which the target node is supposed to act, and this will bring new system error if the assumption is not correct. Considering this, we first create three fuzzy sets using three KFs whose state matrix stand for different motion patterns, then linearly combined the memberships of a target node of the fuzzy sets. Finally, simulation results show that the PRKF can enhance the localization accuracy about more than 20%. (C) 2009 Elsevier Inc. All rights reserved.
部门归属导航与通信研究室
关键词Time Delay Of Arrival Fuzzy Set Membership Function Pattern
收录类别SCI
语种英语
WOS记录号WOS:000278690300019
引用统计
文献类型期刊论文
条目标识符http://210.72.145.45/handle/361003/4772
专题导航与通信研究室
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GB/T 7714
Han Tao,Lu Xiaochun,Lan Qi. Pattern recognition based Kalman filter for indoor localization using TDOA algorithm[J]. APPLIED MATHEMATICAL MODELLING,2010,34(10):2893-2900.
APA Han Tao,Lu Xiaochun,&Lan Qi.(2010).Pattern recognition based Kalman filter for indoor localization using TDOA algorithm.APPLIED MATHEMATICAL MODELLING,34(10),2893-2900.
MLA Han Tao,et al."Pattern recognition based Kalman filter for indoor localization using TDOA algorithm".APPLIED MATHEMATICAL MODELLING 34.10(2010):2893-2900.
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