This article presents a novel sensor-fusion method for indoor vehicle tracking. The phase of the signals backscattered by a set of Ultra High Frequency-Radio Frequency Identification (UHF-RFID) reference tags spread in the scenario is combined with the information acquired by on-board low-cost kinematic sensors. The RFID data are acquired by the on-board reader, during the relative motion of the vehicle with respect to the static reference tags, by resembling a synthetic-array approach, with an advantageous reduction of the reference-tag spatial density. In particular, such phase samples are combined with the kinematic data collected by odometers, through a sensor-fusion approach. The method capability is investigated through a numerical analysis that accounts for the main system parameters. Then, the tracking capability is demonstrated through a measurement campaign in a laboratory test set with a UHF-RFID robot prototype equipped with commercial encoders. Experimental results show an average localization error of centimeter order in the estimation of medium-length trajectories by employing only two reference tags in a relatively small area. The proposed method does not need for any calibration procedure and can be implemented by commercial off-the-shelf (COTS) hardware.