Extended Kalman Filter for wireless LAN based indoor positioning

被引：68

作者：

Yim, Jaegeol ^{[2
]}

Park, Chansik ^{[3
]}

Joo, Jaehun ^{[1
]}

Jeong, Seunghwan ^{[2
]}

机构：

[1] Dongguk Univ, Dept Elect Commerce, Gyeongju 780714, Gyeongbuk, South Korea

[2] Dongguk Univ, Dept Comp & Multimedia, Gyeongju 780714, Gyeongbuk, South Korea

[3] Chungbuk Natl Univ, Sch Elect & Comp Engn, Cheongju 361763, Chunbuk, South Korea

来源：

DECISION SUPPORT SYSTEMS | 2008年 / 45卷 / 04期

关键词：

Indoor positioning; Extended Kalman Filter; Wireless Local Area Network; Fingerprinting method; K-NN; Bayesian method; Decision tree; Trilateration;

D O I：

10.1016/j.dss.2008.03.004

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A WLAN (Wireless Local Area Network) based Extended Kalman Filter (EKF) method lot indoor positioning is introduced in this paper. WLAN based indoor positioning is more economical than other methods because it does not require any special equipment dedicated to positioning. The most popular technique used for indoor positioning is the fingerprinting method, but the EKF method is easier to deploy because, unlike fingerprinting, it does not require a time consuming off-line phase. This paper also provides experimental comparisons of our EKF method with other indoor positioning methods. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：960 / 971

页数：12

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