The millimeter wave (mmWave) radar sensing-aided communications in vehicular mobile communication systems is investigated. To alleviate the beam training overhead under high mobility scenarios, a successive pose estimation and beam tracking (SPEBT) scheme is proposed to facilitate mmWave communications with the assistance of mmWave radar sensing. The proposed SPEBT scheme first resorts to a Fast Conservative Filtering for Efficient and Accurate Radar odometry (Fast-CFEAR) approach to estimate the vehicle pose consisting of 2-dimensional position and yaw from radar point clouds collected by mmWave radar sensor. Then, the pose estimation information is fed into an extend Kalman filter to perform beam tracking for the line-of-sight channel. Owing to the intrinsic robustness of mmWave radar sensing, the proposed SPEBT scheme is capable of operating reliably under extreme weather/illumination conditions and large-scale global navigation satellite systems (GNSS)-denied environments. The practical deployment of the SPEBT scheme is verified through rigorous testing on a real-world sensing dataset. Simulation results demonstrate that the proposed SPEBT scheme is capable of providing precise pose estimation information and accurate beam tracking output, while reducing the proportion of beam training overhead to less than 5% averagely.

翻译：研究了毫米波（mmWave）雷达感知辅助的车载移动通信系统。为缓解高机动场景下的波束训练开销问题，提出了一种基于毫米波雷达感知辅助的连续姿态估计与波束跟踪（SPEBT）方案。该方案首先采用快速保守滤波的高效精确雷达里程计（Fast-CFEAR）方法，从毫米波雷达传感器采集的点云中估计车辆姿态（包括二维位置和偏航角）；随后将姿态估计信息输入扩展卡尔曼滤波器，以实现视距信道的波束跟踪。由于毫米波雷达感知具有内在鲁棒性，所提SPEBT方案能在极端天气/光照条件以及大规模全球导航卫星系统（GNSS）拒止环境中可靠运行。通过在真实感知数据集上的严格测试，验证了SPEBT方案的实用部署能力。仿真结果表明，该方案能提供精确的姿态估计信息和准确的波束跟踪输出，同时将波束训练开销比例平均降低至5%以下。