Near-Field Integrated Sensing and Communication: Beam Tracking for UAV

A novel near-field beam tracking approach for unmanned aerial vehicle (UAV) is proposed based on integrated sensing and communication (ISAC) system. We consider base station (BS) is equipped with extremely large-scale antenna arrays (ELAA), which greatly increases the near-field range. Assuming the UAV is located in the near-field region, we develop the communication and sensing signal models. Building on this foundation, we propose an extended Kalman filter (EKF)-based beam tracking algorithm to efficiently achieve beam alignment between the BS and UAV. To be more specific, we first form the state evolution and measurement models for the UAV, and further calculate the Jacobian matrices to execute the EKF process. Furthermore, we consider the jittering effect that UAV is typically affected by gusts of wind in practical environments. In order to compensate the jittering effect, we propose a segmentation search-based beam tracking (SSB) algorithm. In particular, we first formulate the optimization problem to compensate for the pitch jittering of UAV, aiming to maximize the signal-to-noise ratio (SNR) of receiving signal while searching within a certain angle range. Then, we propose a segmentation search algorithm to solve the problem, acquiring global optimal solution. Simulation results confirm the effectiveness of the proposed schemes, demonstrating outstanding performance with respect to the achievable rate and tracking accuracy within near-field region.