Abstract: ［Objective］ Currently, wireless environment detection for urban rail transit vehicle-wayside communication primarily relies on manual testing with instruments, which is labor-intensive and inefficient. To meet the needs for intelligent and routine monitoring of the vehicle-wayside wireless communication environment, it is necessary to construct a wireless fingerprint library for this issue to enable the real-time monitoring. ［Method］ The conceptualization and process of establishing the wireless fingerprint library for vehicle-wayside communication is elaborated. The wireless reception areas of metro lines are divided into numerous grids at appropriate intervals. Wireless monitoring equipment installed on metro trains collects real-time data on the vehicle-wayside communication wireless environment for each grid. By employing various encoding methods and introducing Mahalanobis distance, the characteristic data are processed, the wireless feature information for each grid is extracted and then recorded into the corresponding grid area to form wireless fingerprint library. The library utilizes the DeepFS algorithm, enabling adaptive updates of the wireless feature data for each grid. The application of the wireless fingerprint library in urban rail transit vehicle-wayside communication is illustrated through specific examples. ［Result & Conclusion］ By comparing real-time monitoring data with the wireless fingerprint information in the library, abnormalities in the vehicle-wayside wireless communication environment can be promptly detected. This effectively enhances the maintenance level of urban rail transit vehicle-wayside wireless communication environment.