Deploying integrated sensing and communication (ISAC) technology in future Internet of Drones (IoD) networks is a significant trend. In this paper, we investigate the exploration of ISAC signals within IoD networks, enabling Unmanned Aerial Vehicles (UAVs) to engage in vehicle trajectory tracking and communication. Taking into account real-world road constraints and scenarios of non-continuous communication, we propose a grid model and leverage the Hidden Markov Model (HMM) for tracking vehicle trajectories, while conducting channel estimation at the vehicle using ISAC signals. Simulation results demonstrate a notable performance enhancement of the proposed scheme compared to baseline method relying on direct rounding decisions, particularly in low SNR conditions.


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    Title :

    UAV-Assisted Vehicular Trajectory Tracking Using HMM in Integrated Sensing and Communication System


    Contributors:
    Ma, Zhongmin (author) / Du, Qinghe (author) / Xia, Linzhong (author) / Zhang, Jintao (author) / Lu, Chen (author)


    Publication date :

    2025-05-12


    Size :

    412319 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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