Cellular vehicle-to-everything(C-V2X), as a representative communication technology for intelligent connected vehicles, enables data interaction between vehicle-to-vehicle, vehicle-to-infrastructure, and vehicle-to-pedestrian by establishing highly reliable communication links. However, the complex and variable communication environment of the internet of vehicles poses significant challenges to terminal identity access. Due to its characteristics of uniqueness, stability, and unclonability, radio frequency fingerprint (RFF) can provide a physical layer security solution for C-V2X terminal identity access. Based on this, this paper proposes a C-V2X terminal radio frequency fingerprint extraction and authentication scheme: First, an effective preprocessing algorithm is designed to separate the demodulation reference signal (DMRS) in the physical sidelink shared channel (PSSCH) and the physical sidelink control channel (PSCCH); a logarithmic spectrum separation algorithm is adopted to suppress the noise components caused by the randomization of the DMRS sequence; a training method based on the siamese adversarial network (SANet) is designed to make the feature extraction network focus on extracting hardware-related device fingerprints. Experimental results show that the designed preprocessing and logarithmic spectrum denoising algorithms can effectively improve the stability and recognition accuracy of terminal fingerprints in multiple scenarios; the SANet exhibits excellent generalization ability in cross-channel environment tests: The average authentication precision and recall reach 93.22% and 92.67% in static scenarios, and 82.85% and 82.21% in mobile scenarios, respectively.