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24 May 2022 An improved indoor localization algorithm based on SOM and WKNN
Jiuqi Luo, Changgeng Li
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Proceedings Volume 12260, International Conference on Computer Application and Information Security (ICCAIS 2021); 1226009 (2022) https://doi.org/10.1117/12.2637408
Event: International Conference on Computer Application and Information Security (ICCAIS 2021), 2021, Wuhan, China
Abstract
This paper focuses on WiFi indoor positioning based on received signal strength, and weighed K-nearest neighbor (WKNN) algorithm is the most classic position estimation strategy. However, locating across the entire fingerprint database takes a lot of time. In this paper, a clustering algorithm based on Self-Organization Map (SOM) is proposed to shorten the positioning time. Meanwhile, an improved WKNN algorithm is proposed to further increase the positioning accuracy. The experiment results show that the positioning time is effectively cut down after clustering and the average positioning error of the proposed algorithm is 1.18 m, which can achieve high accuracy in indoor environment.
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Jiuqi Luo and Changgeng Li "An improved indoor localization algorithm based on SOM and WKNN", Proc. SPIE 12260, International Conference on Computer Application and Information Security (ICCAIS 2021), 1226009 (24 May 2022); https://doi.org/10.1117/12.2637408
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KEYWORDS
Received signal strength
Databases
Physics
Electronics
Global Positioning System
Receivers
Satellites
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