Near-Field Beamforming With 3D Velocity Sensing and Localization for Uav Communications

The real-time near-field beamforming framework with the aided of 3D velocity sensing and localization for unmanned aerial vehicle (UAV) communications is proposed. Exploiting the variant Doppler shift over the spatial domain in the near field, the three-dimensional (3D) velocities are estimated with the echo signals. To provide timely correction of the location prediction errors with the estimated velocities, the extended Kalman filter (EKF) is adopted to fuse the predicted states and the estimated ones. Subsequently, the near-field beamforming can be conducted with the predicted locations of the UAV, thereby realizing zero-pilot and low-latency transmission. Numerical results unveil that, the proposed scheme can achieve the accurate tracking of the UAV's flying route.