An enhanced UWB-based range/GPS cooperative positioning approach using adaptive variational Bayesian cubature Kalman filtering

Abstract

Precise position awareness is a fundamental requirement for advanced applications of emerging intelligent transportation systems, such as collision warning and speed advisory system. However, the achievable level of positioning accuracy using global navigation satellite systems does not meet the requirements of these applications. Fortunately, cooperative positioning (CP) techniques can improve the performance of positioning in a vehicular ad hoc network (VANET) through sharing the positions between vehicles. In this paper, a novel enhanced CP technique is presented by combining additional range-ultra-wide bandwidth- (UWB-) based measurements. Furthermore, an adaptive variational Bayesian cubature Kalman filtering (AVBCKF) algorithm is proposed and used in the enhanced CP method, which can add robustness to the time-variant measurement noise. Based on analytical and experimental results, the proposed AVBCKF-based CP method outperforms the cubature Kalman filtering- (CKF-) based CP method and extended Kalman filtering- (EKF-) based CP method.