Bisecting K-Means Based Fingerprint Indoor Localization

Yuxing Chen; Wei Liu; Haojie Zhao; Shuling Cao; Shasha Fu; Dingde Jiang

Simulation Tools and Techniques. 11th International Conference, SIMUtools 2019, Chengdu, China, July 8–10, 2019, Proceedings

Research Article

Bisecting K-Means Based Fingerprint Indoor Localization

Download

187 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-030-32216-8_1,
    author={Yuxing Chen and Wei Liu and Haojie Zhao and Shuling Cao and Shasha Fu and Dingde Jiang},
    title={Bisecting K-Means Based Fingerprint Indoor Localization},
    proceedings={Simulation Tools and Techniques. 11th International Conference, SIMUtools 2019, Chengdu, China, July 8--10, 2019, Proceedings},
    proceedings_a={SIMUTOOLS},
    year={2019},
    month={10},
    keywords={Fingerprint Bisecting K-means WiFi Indoor localization},
    doi={10.1007/978-3-030-32216-8_1}
}

Yuxing Chen
Wei Liu
Haojie Zhao
Shuling Cao
Shasha Fu
Dingde Jiang
Year: 2019
Bisecting K-Means Based Fingerprint Indoor Localization
SIMUTOOLS
Springer
DOI: 10.1007/978-3-030-32216-8_1

Yuxing Chen¹^,*, Wei Liu¹^,*, Haojie Zhao¹^,*, Shuling Cao¹^,*, Shasha Fu¹^,*, Dingde Jiang²^,*

1: Xidian University
2: University of Electronic Science and Technology of China

*Contact email: yxchen_2@stu.xidian.edu.cn, liuweixd@mail.xidian.edu.cn, hjzhao@stu.xidian.edu.cn, slcao_cn@stu.xidian.edu.cn, ssfu@stu.xidian.edu.cn, jiangdd99@sina.com

Abstract

This paper presents a fingerprint indoor localization system based on Bisecting k-means (BKM). Compared to k-means, BKM is a more robust clustering algorithm. Specifically, BKM based indoor localization consists of two stages: offline stage and online positioning stage. In the offline stage, BKM is used to divide all the reference points (RPs) into clusters. A series of experiments have been made to show that our system can greatly improve localization accuracy.

Keywords: Fingerprint Bisecting K-means WiFi Indoor localization

Published: 2019-10-24
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-030-32216-8_1