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Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings

Research Article

Weight Matrix Analysis Algorithm for WLAN Indoor Positioning System

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  • @INPROCEEDINGS{10.1007/978-3-030-00557-3_32,
        author={Lin Ma and Jian Li and Yubin Xu},
        title={Weight Matrix Analysis Algorithm for WLAN Indoor Positioning System},
        proceedings={Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings},
        proceedings_a={MLICOM},
        year={2018},
        month={10},
        keywords={Indoor positioning WLAN Radio map Weight matrix analysis},
        doi={10.1007/978-3-030-00557-3_32}
    }
    
  • Lin Ma
    Jian Li
    Yubin Xu
    Year: 2018
    Weight Matrix Analysis Algorithm for WLAN Indoor Positioning System
    MLICOM
    Springer
    DOI: 10.1007/978-3-030-00557-3_32
Lin Ma1,*, Jian Li1, Yubin Xu1
  • 1: Harbin Institute of Technology
*Contact email: malin@hit.edu.cn

Abstract

Because WLAN signal strength data is vulnerable to external interference and its validity period is short-lived, it is necessary to reconstruct radio map to improve positioning performance. We add the weight data to the original fingerprint library, which is obtained by the reliability of information. Using it, we can know the importance of neighborhood points selected in the online phase and get better positioning performance. In the positioning phase, the KD tree is added to improve the positioning efficiency of the positioning algorithm. Finally, the positioning accuracy and efficiency can be improved.

Keywords
Indoor positioning WLAN Radio map Weight matrix analysis
Published
2018-10-12
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-00557-3_32
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