Mobile Feature Enhanced High-Accuracy Positioning Based on Carrier Phase and Bayesian Estimation

Abstract

The mobile feature and the moving positions are important for mobile communications and Internet of Things. Inspired by the potentially excellent precision of carrier phase positioning, this article proposes a mobile feature enhanced high-accuracy positioning algorithm based on the carrier phase and Bayesian estimation. The mobile feature is first estimated using time-differential carrier phase measurements. By combining the estimated position changes with instant ranging and carrier phase measurements, the factorized posterior probability of positioning is established based on the Bayes theorem. In turn, a factor graph-based positioning method is proposed to obtain precise positioning results. The numerical simulation results show that the proposed algorithm can achieve centimeter-level accuracy, and the positioning error can approach the Cramer–Rao lower bound.