Sensing Aided Beam Tracking for UAV With Jittering Effect

The development of sixth generation (6G) wireless technology presents numerous pivotal scenarios, among which the integrated sensing and communication (ISAC) for unmanned aerial vehicles (UAVs) is attracting significant attention. In practice, UAV communication often faces challenges due to the unavoidable jitter caused by inherent random gusts, which can lead to beam misalignment. This letter proposes an algorithm combining extended Kalman filter (EKF) with enhanced particle swarm optimization (EPSO) for beam tracking of a jittering UAV from an integrated radar and communication platform (IRCP). Simulation results show that our proposed algorithm not only improves the accuracy of beam tracking but also balances the impact of UAVs' jitter on communication performance, compared with the conventional feedback-based beam tracking method.