Two-step calibration for UWB-based indoor positioning system and positioning filter considering channel common bias

Abstract

The channel error for ranging-based positioning generally considers the scale-factor error and bias. In this paper, the installation location error of anchor nodes (ANs) is additionally considered. To estimate these errors independently, a two-step calibration method is proposed. However, bias may vary depending on the changing indoor environment due to the non-line-of-sight error. Therefore, it is necessary to estimate bias in real-time at the positioning step. In this paper, a channel common bias (CCB) is defined, and a filter that can estimate not only the location of the mobile node but also the CCB is designed based on cubature Kalman filter (CKF). Experimental results show that the proposed two-step calibration method can accurately estimate scale-factor error and bias per channel, and location errors of all ANs. Also, it shows that the proposed CKF-based positioning filter considering CCB has faster channel error estimation performance than the filter considering channel-specific bias.