Mann-Whitney Rank Sum Test Based Wireless Local Area Network Indoor Mapping and Localization Approach

Mu ZHOU; Yanmeng WANG; Hui YUAN; Zengshan TIAN

doi:10.11999/JEIT180392

Volume 41 Issue 7

Jul. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(7): 1555-1564

Mu ZHOU, Yanmeng WANG, Hui YUAN, Zengshan TIAN. Mann-Whitney Rank Sum Test Based Wireless Local Area Network Indoor Mapping and Localization Approach[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1555-1564. doi: 10.11999/JEIT180392

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Mu ZHOU, Yanmeng WANG, Hui YUAN, Zengshan TIAN. Mann-Whitney Rank Sum Test Based Wireless Local Area Network Indoor Mapping and Localization Approach[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1555-1564. doi: 10.11999/JEIT180392

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Mann-Whitney Rank Sum Test Based Wireless Local Area Network Indoor Mapping and Localization Approach

doi: 10.11999/JEIT180392

School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (61771083, 61704015), The Postgraduate Scientific Research and Innovation Project of Chongqing (CYS17221, CYS18240), The Program for Changjiang Scholars and Innovative Research Team in University (IRT1299), The Fundamental and Frontier Research Project of Chongqing (cstc2017jcyjAX0380, cstc2015jcyjBX0065), The University Outstanding Achievement Transformation Project of Chongqing (KJZH17117)

Received Date: 2018-04-26
Rev Recd Date: 2019-03-08

Available Online: 2019-03-28

Publish Date: 2019-07-01

Abstract

Abstract

The Mann-Whitney rank sum test based Wireless Local Area Network (WLAN) indoor mapping and localization approach is proposed. Firstly, according to the localization accuracy requirement, this approach performs the motion paths segmentation in target area, and meanwhile merges the similar motion path segments based on the Mann-Whitney rank sum test. Then, a signal clustering algorithm based on the similar Received Signal Strength (RSS) sequence segments is adopted to guarantee the physical adjacency of the RSS samples in the same cluster. Finally, the backbone nodes based diffusion mapping is used to construct the mapping relations between the physical and signal spaces, and the motion user localization is consequently achieved. The experimental results indicate that compared with the existing WLAN indoor mapping and localization approaches, the proposed one is able to achieve higher mapping and localization accuracy without motion sensor assistance or location fingerprint database construction.
- Wireless Local Area Network (WLAN),
- Indoor localization,
- Behavior analysis,
- Mann-Whitney rank sum test,
- Space mapping

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References(32)

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