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 k clusters. A series of experiments have been made to show that our system can greatly improve localization accuracy.
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CITATION STYLE
Chen, Y., Liu, W., Zhao, H., Cao, S., Fu, S., & Jiang, D. (2019). Bisecting K-Means Based Fingerprint Indoor Localization. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 295 LNICST, pp. 1–12). Springer. https://doi.org/10.1007/978-3-030-32216-8_1
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