Multipath Mitigation Algorithm for Multifrequency-Based Ranging via Convex Relaxation in Passive UHF RFID

Abstract

Radio frequency identification (RFID) is a promising technology in indoor localization. However, multipath cannot be avoided in indoor passive ultrahigh frequency RFID localization environment, which results in poor localization accuracy. In this paper, a range-based localization scheme has been developed to mitigate the effect of multipath errors and improve the localization accuracy. The proposed localization methods are based on semi-definite programming and second-order cone programming and do not require any statistics of multipath error. First, all the phase information of multifrequency is utilized. Dual-frequency phase difference of all dual-frequency combinations can be obtained to range. The ranging error is assumed to follow the Gaussian distribution. Then, convex relaxation methods with limiting the mean ranging error to one standard deviation of the Gaussian distribution are proposed. Finally, in order to solve the feasibility problem, the constraint of the mean ranging error is relaxed. Simulation results demonstrate that the proposed methods outperform some existing localization algorithms in multipath environment.