Weight Matrix Analysis Algorithm for WLAN Indoor Positioning System

Lin Ma; Jian Li; Yubin Xu

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

Download

136 downloads

Cite: BibTeX Plain Text

@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

Weight Matrix Analysis Algorithm for WLAN Indoor Positioning System

Abstract

About EAI

Community

Publish with EAI