Cooperative Positioning Algorithms for Estimating Inter-Vehicle Distance Using Multi-GNSS

Abstract

In this paper, non ranging-based cooperative positioning algorithms based on GNSS measurements, including Absolute Position Differencing (APD), Single-Differencing (SD), and Double-Differencing (DD), are used to estimate the intervehicle distance (IVD). To reduce the uncertainty of IVD estimates, the maximum volume algorithm (MVA) was employed to determine the optimal geometric group composition of four satellites as a multi-GNSS system, namely GPS, GLONASS, Galileo, and BeiDou. Real-world experiments on two autonomous vehicles using SD-based and DD-based algorithms demonstrate that estimated IVD uncertainty is sub-centimetres, which is close to sensor-based solutions but at a lower cost.