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.
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Acknowledgment
This paper is supported by National Natural Science Foundation of China (61571162), Ministry of Education - China Mobile Research Foundation (MCM20170106) and Heilongjiang Province Natural Science Foundation (F2016019).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Ma, L., Li, J., Xu, Y. (2018). Weight Matrix Analysis Algorithm for WLAN Indoor Positioning System. In: Meng, L., Zhang, Y. (eds) Machine Learning and Intelligent Communications. MLICOM 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-030-00557-3_32
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DOI: https://doi.org/10.1007/978-3-030-00557-3_32
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