An improved k-NN algorithm for localization in multipath environments

Abstract

To improve the localization accuracy in multipath environments, this paper presents an effective localization approach with the utilization of reference tags. In this approach, an improved k-nearest neighbor (k-NN) algorithm is proposed based on radio-frequency (RF) phases. The traditional k-NN algorithm only focuses on the weighting factors of the coordinates of the selected reference tags, while the improved k-NN algorithm aims at the estimation of direct distance from a reader antenna to a target tag. Then, the location is estimated by linear least squares with a new reference selection scheme. Simulation results show that our approach is superior to the traditional localization approaches under multipath environments. In addition, we conclude that phase has the superiority over strength in the selection of reference tags for range estimation, and range estimation is more accurate than coordinate estimation with k-NN algorithm for localization.