IRS-Assisted Collaborative Tracking for ISAC in Vehicular Networks

To address the challenges of restricted Vehicle-to-Everything (V2X) communication and sensing paths caused by dense urban environments in 6G vehicular networks, an IRS-assisted ISAC-V2X system framework is proposed. Considering vehicle mobility under non-line-of-sight (NLoS) conditions, intelligent reflective surfaces (IRS) are employed to dynamically adjust signal propagation paths, assisting the transmission of integrated sensing and communication (ISAC) signals. The extended Kalman filter algorithm is utilized in conjunction with real-time channel state information from ISAC echo signals to track and predict the positions of moving vehicles. Simulation results demonstrate that the proposed system significantly enhances the accuracy and robustness of beam tracking and positioning under NLoS conditions.