Attitude Estimation Assisted Short-Range UAV Localization and Tracking Based on Extremely Large Antenna Array
Xinhong Dai, Mingchen Zhang, Boyu Teng, Xiaojun Yuan, Xin Wang · IEEE Transactions on Wireless Communications · 2025
The attitude of an unmanned aerial vehicle (UAV) is highly related to its motion status, such as velocity and acceleration, and thus needs to be taken into consideration in UAV localization and tracking. In this paper, we study a short-range UAV localization and tracking system, where a UAV flies in the near-field region of an extremely large antenna array (ELAA). The ELAA is arranged to track the UAV by continuously estimating its position and attitude. To accomplish this task, we leverage an array partitioning approach to establish the signal model between the UAV and the ELAA based on the subarray-wise far-field assumption. Then, we characterize the relationship between UAV’s attitude and motion status based on force analysis. Building on the analysis, we formulate a probabilistic UAV tracking problem that jointly estimates the UAV position and attitude in an online fashion. A new message-passing-based algorithm is proposed to solve this problem, which combines attitude and motion status information to enhance tracking performance. We also derive the Bayesian Cramér Rao bound (BCRB) of the problem as a performance benchmark. Numerical results show that the proposed algorithm outperforms other alternatives, and demonstrate that the information fusion of the UAV attitude and motion status can effectively improve the accuracy of the UAV localization and tracking.