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 maneuverable UAVs. In this letter, we propose a novel interacting multiple model with enhanced unscented Kalman filter (IMM-EUKF) algorithm to realize 3D beam tracking for one maneuverable UAV within the framework of DFRC. To be specific, we build multiple state transition models to adopt the maneuverability of the UAV. Meanwhile, the stability of the unscented Kalman filter (UKF) is improved by using the singular value decomposition (SVD). Simulation results show that the proposed algorithm has higher tracking accuracy and better transmission performance for one maneuverable UAV than the traditional single-motion model based beam tracking algorithm.

In this letter, we propose a velocity measurement algorithm based on auto-correlation in a single frame for IEEE 802.11ad. The periodicity of the Golay sequences in the preamble is exploited in the algorithm to estimate the time delay and achieve the velocity measurement at the same time. The improved measuring accuracy is obtained as the effection of noise is suppressed by designing and utilizing the auto-correlation function.