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    RSSI indoor localization through a Bayesian strategy

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    Authors
    Zhou, Fu
    Lin, Kaixian
    Ren, Aifeng
    Cao, Dongjian
    Zhang, Zhiya
    Ur-Rehman, Masood
    Yang, Xiaodong
    Alomainy, Akram
    Affiliation
    Xidian University
    University of Bedfordshire
    Queen Mary College University of London
    Issue Date
    2017-10-02
    Subjects
    radio propagation
    Zigbee
    Bayesian theorem
    RSSI
    Gaussian distribution
    maximum likelihood estimation
    Bayes methods
    
    Metadata
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    Abstract
    A method to locate the position of the user in an indoor environment employing Bayesian theory is presented in this paper. A detailed analysis of the positional accuracy is carried out evaluating effects of two major degradation factors namely the measurement and calculation errors. The proposed technique makes use of the Gaussian distribution of random data in indoor Zigbee propagation model based on received signal strength indicator (RSSI) and the triangular positioning algorithm, maximum likelihood estimation (MLE) and Bayesian theory. It identifies the user's location calculating the maximum probability point. The proposed method offers high accuracy levels with a mean error of 0.1363m as compared to the mean error values of 1.4059m and 0.4291m for the triangular localization and triangular localization with MLE methods, respectively.
    Citation
    Zhou F, Lin K, Ren A, Cao D, Zhang Z, Ur Rehman M, Yang X, Alomainy A (2017) 'RSSI indoor localization through a Bayesian strategy', IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) - Chongqing, IEEE.
    Publisher
    IEEE
    URI
    http://hdl.handle.net/10547/623856
    DOI
    10.1109/IAEAC.2017.8054360
    Additional Links
    https://ieeexplore.ieee.org/document/8054360
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1109/IAEAC.2017.8054360
    Scopus Count
    Collections
    Computing

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