Abstract
The k-nearest neighbor (KNN) based indoor localization methods are practical to the wireless sensor network constructed by internet of things. The weighted KNN (WKNN) method is designed as the enhanced KNN but actually does not outperform KNN. Inspired by the technique of differential coordinates from satellite-based localization, in this paper we propose the differential coordinate based WKNN (DC-WKNN) using Wi-Fi technology to further improve the accuracy for WKNN by canceling the localization error calculated between the position of the first and the second WKNN estimated coordinates. Simulation results show that the proposed DC-WKNN provides higher accuracy than both WKNN and KNN for the dense reference point localization area.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
