Specific emitter identification (SEI) enables physical-layer authentication of wireless devices by exploiting hardware-induced radio-frequency (RF) fingerprints embedded in received signals. However, existing deep learning–based SEI methods often suffer from limited cross-domain generalization, as models tend to overfi...
Lu-Yao Wang, Zhen-Xin Cai, Fan Wang et al.· IEEE Transactions on Cogniti...· 0 citations
Accurate identification of uncrewed aerial vehicles (UAVs) is crucial to ensure airspace security and effective threat assessment. Traditional UAV classification systems usually rely on single-modal sensing data, which limits their ability to capture the diversity and complementarity of UAV characteristics under differ...
Rui Wang, Siqi Lou, Zhen-Xin Cai et al.· IEEE Transactions on Cogniti...· 0 citations
Uncrewed aerial vehicle (UAV) radio frequency fingerprint identification (RFFI) is a promising technique for noncooperative UAV management. However, models trained under line-of-sight (LOS) conditions suffer from significant performance degradation when deployed in complex non-line-of-sight (NLOS) scenarios due to chan...