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Radius based domain clustering for WiFi indoor positioning

作者:Zhang, W (Zhang, Wei)^{[ 1 ]} ; Hua, XH (Hua, Xianghong)^{[ 1 ]} ; Yu, KG (Yu, Kegen)^{[ 1 ]} ; Qiu, WN (Qiu, Weining)^{[ 1 ]} ; Chang, X (Chang, Xin)^{[ 1 ]} ; Wu, B (Wu, Bang)^{[ 1 ]} ; Chen, XJ (Chen, Xijiang)^{[ 1,2,3 ]}

SENSOR REVIEW

DOI: 10.1108/SR-06-2016-0102

出版年: 2017

摘要

Purpose - Nowadays, WiFi indoor positioning based on received signal strength (RSS) becomes a research hotspot due to its low cost and ease of deployment characteristics. To further improve the performance of WiFi indoor positioning based on RSS, this paper aims to propose a novel position estimation strategy which is called radius-based domain clustering (RDC). This domain clustering technology aims to avoid the issue of access point (AP) selection.

Design/methodology/approach - The proposed positioning approach uses each individual AP of all available APs to estimate the position of target point. Then, according to circular error probable, the authors search the decision domain which has the 50 per cent of the intermediate position estimates and minimize the radius of a circle via a RDC algorithm. The final estimate of the position of target point is obtained by averaging intermediate position estimates in the decision domain.

Findings - Experiments are conducted, and comparison between the different position estimation strategies demonstrates that the new method has a better location estimation accuracy and reliability.

Research limitations/implications - Weighted k nearest neighbor approach and Naive Bayes Classifier method are two classic position estimation strategies for location determination using WiFi fingerprinting. Both of the two strategies are affected by AP selection strategies and inappropriate selection of APs may degrade positioning performance considerably.

Practical implications - The RDC positioning approach can improve the performance of WiFi indoor positioning, and the issue of AP selection and related drawbacks is avoided.

Social implications - The RSS-based effective WiFi indoor positioning system can makes up for the indoor positioning weaknesses of global navigation satellite system. Many indoor location-based services can be encouraged with the effective and low-cost positioning technology.

Originality/value - A novel position estimation strategy is introduced to avoid the AP selection problem in RSS-based WiFi indoor positioning technology, and the domain clustering technology is proposed to obtain a better accuracy and reliability.

作者关键词:Domain clustering; Naive Bayes classifier; Received signal strength; Weighted k nearest neighbour; WiFi indoor positioning

KeyWords Plus:ACCESS-POINT SELECTION; LOCATION; SYSTEM; FI; TRACKING; STRATEGY

通讯作者地址: Hua, XH (通讯作者)

地址:

电子邮件地址:[email protected]

基金资助机构授权号

EMERALD GROUP PUBLISHING LTD, HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND

研究方向:Instruments & Instrumentation

Web of Science 类别:Instruments & Instrumentation

文献类型:Article

语种:English

入藏号: WOS:000395709000007

ISSN: 0260-2288

eISSN: 1758-6828

Impact Factor (影响因子): 0.898