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http://dx.doi.org/10.7236/JIIBC.2017.17.6.105

A Study on the Weight of W-KNN for WiFi Fingerprint Positioning  

Oh, Jongtaek (Dept. of Electronics Information Eng., Hansung University)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.17, no.6, 2017 , pp. 105-111 More about this Journal
Abstract
In this paper, the analysis results are shown about several weights of Weighted K-Nearest Neighbor method, Recently, it is employed for the indoor positioning technologies using WiFi fingerprint which has been actively studied. In spite of the simplest feature, the W-KNN method shows comparable performance to another methods using WiFi fingerprint technology. So W-KNN method has employed in the existing indoor positioning system. It shows positioning error performance according to data preprocessing and weight factor, and the analysis on the weight is very important. In this paper, based on the real measured WiFi fingerprint data, the estimation error is analyzed and the performances are compared, for the case of data processing methods, of the weight of average, variance, and distance, and of the averaging several position of number K. These results could be practically useful to construct the real indoor positioning system.
Keywords
WiFi fingerprint; W-KNN; indoor positioning; smartphone;
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