A Vehicle Positioning Method Based on Joint TOA and DOA Estimation with V2R Communications

This paper presents a vehicle positioning method based on joint estimation of time of arrival (TOA) and direction of arrival (DOA) with Vehicle-to-Roadside (V2R) communications. By analyzing the measured channel frequency response (CFR) between vehicles and the roadside unit (RU), the enhanced two-dimensional matrix pencil (2-D MP) algorithm is implemented to design the parameter estimator, which has lower complexity without forming a covariance matrix. The position coordinates of vehicles can then be calculated from the estimates. To improve the positioning accuracy, the extended Kalman filtering (EKF) is further introduced for mitigating the noise influence and estimating error. Simulation results show that the proposed method can achieve better positioning estimation compared with the Global Positioning System (GPS) and inertial navigation systems (INS) fusion method.