Robust Beam Tracking for 3D Manoeuvrable UAV in DFRC Systems

Dual-functional radar-communication (DFRC) will be a key technology in future sixth-generation (6G) network. Specifically, an integrated radar and communication platform (IRCP) equipped with full-dimensional antenna arrays can execute 3D beamforming, which can effectively minimize interference for communicating with unmanned aerial vehicles (UAVs). However, a significant challenge in fully exploiting 3D beamforming gain is the IRCP's ability to precisely track manoeuvrable UAVs. In this letter, we propose a novel interacting multiple model with enhanced unscented Kalman filter algorithm to realize 3D beam tracking for one manoeuvrable UAV within the framework of DFRC. To be specific, we build multiple state transition models to adopt the manoeuvrability of the UAV. Meanwhile, the stability of the unscented Kalman filter is improved by using the singular value decomposition. Simulation results show that the proposed algorithm has higher tracking accuracy and better transmission performance for one manoeuvrable UAV than the traditional single-motion model based beam tracking algorithm.