Precise Angle Estimation by Jointly Using Spatial/Temporal Change of Channel State Information and Its Application in Pedestrian Positioning

Previously, we have proposed a pedestrian positioning method that uses vehicles near a pedestrian as anchors, and combines vehicle-to-vehicle (V2V) communication signals and GPS signals for high precision positioning. In this method, pedestrian-vehicle distance and angle of arrival (AoA) are estimated from the channel state information (CSI) of vehicular signals and used in position computation, but the precision of angle estimation is limited due to the small number of antennas that can be mounted on a mobile device. To solve this problem, in this paper, we propose a new method to estimate AoA precisely by jointly using spatial change of CSI at multiple antennas and temporal change of CSI per antenna (caused by pedestrian/vehicle movement), and on this basis improve pedestrian positioning precision. Specifically, a two-dimensional antenna array is constructed from CSI acquired from multiple antennas/timings, and the MUSIC method with spatial smoothing is applied to estimate AoA. 3D ray tracing simulations with real 3D map confirm that the proposed method can effectively improve the precision of angle estimation and reduce positioning error when only a small number of antennas are available at a pedestrian device, and the performance increases with the number of antennas.