A novel jitter-robust integrated sensing and communication (ISAC)-enabled beam tracking framework is proposed for unmanned aerial vehicle (UAV)-to-UAV (U2U) communication systems. In particular, a tethered UAV base station (UAV-B) serves a maneuvering UAV user (UAV-U), where jitter disrupts beam alignment and degrades communication rates. To enable beam alignment, a UAV-U angle tracking method is first proposed to estimate the relative angles between UAV-B and UAV-U. Specifically, the tethered UAV-B leverages sensing echo signals to obtain motion information of UAV-U, and integrates them with UAV-U’s prior motion models to enhance the accuracy of angle prediction. Meanwhile, through the communication link, UAV-U can receive the direction of UAV-B. Building on the obtained angle information, a jitter compensation algorithm is further developed to maximize the achievable rate of the U2U communication systems. In particular, UAV-B employs adaptive beamwidth control (ABC) to adjust its beamwidth and thus ensures robust coverage for UAV-U. Meanwhile, UAV-U employs beam steering refinement (BSR) to optimize the direction based on predicted angle information, enhancing the received signal-to-noise ratio (SNR) and reducing beam misalignment caused by jitter. Finally, our numerical results unveil that: 1) higher angle prediction accuracy is achieved by the proposed UAV-U angle tracking scheme compared to conventional Kalman filter-based angle tracking methods; and 2) a higher achievable rate in the U2U communication systems is achieved by the proposed jitter compensation scheme compared with traditional beamwidth control-based methods.

Integrated sensing and communication (ISAC), which can exploit the wireless spectrum for concurrent sensing and communication functions, is regarded as a promising technology for the future sixth generation (6G) wireless communication networks. This paper proposes a robust beam tracking method for maneuverable unmanned aerial vehicles (UAVs) with jittering effect within the ISAC framework. By utilizing reflected echoes, the kinematic parameters are measured and the interacting multiple model with extended Kalman filter (IMM-EKF) is designed for robust beam tracking of maneuverable UAVs. Furthermore, due to the jittering effect, the UAV may not point to the optimal alignment direction. To this end, we propose the coordinate descent particle swarm optimization (CDPSO) algorithm to balance the jittering effect by maximizing the received signal-to-noise ratio (SNR) of the UAV. The effectiveness of the proposed scheme is verified via simulation results.