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Abstract ▼ AI-Helper

Research on the technique for estimating the indoor position has been actively carried out. In particular, the WiFi fingerprint method, which does not require any additional infrastructure, is being partially used because of its high economic efficiency. The KNN method which estimates similar points...

Research on the technique for estimating the indoor position has been actively carried out. In particular, the WiFi fingerprint method, which does not require any additional infrastructure, is being partially used because of its high economic efficiency. The KNN method which estimates similar points to the corresponding points by comparing intensity information of the WLAN reception signal measured at various points in advance with intensity information measured at a specific point in the future is simple but has a good performance. However, in the conventional KNN scheme, since the number K of average candidate positions is constant, there is a problem that the position estimation error is not optimized according to a specific point. In this paper, we proposed an algorithm that adaptively changes the K value for each point and applied it to experimental data and evaluated its performance.

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