Radio Frequency Fingerprint Identification Based on Logarithmic Power Cosine Spectrum
نویسندگان
چکیده
With the development of new Internet Things (IoT) applications, such as unmanned ground vehicle (UGV), aerial (UAV), and surface vessel (USV), security wireless device identification is getting more attention. The radio frequency fingerprint (RFF) technology utilizes unique hardware characteristics for identity authentication, which overcomes risks traditional authentication schemes based on distributable keys. In this paper, we propose an RFF scheme logarithmic power cosine spectrum transient signals. We use sliding window variance trajectory-based posterior probability density detection algorithm to improve efficiency signal detection, then adopt discrete Fourier transform extract envelope signal, after that utilize compresses domain features, finally construct 7-dimensional feature vector. For application scenario USV, acquire signals 7 marine automatic systems (AIS) test dataset. experimental results show proposed can achieve ideal recognition accuracy using a Support Vector Machine classifier. Meanwhile, Principal Component Analysis verify vector has good distinguishability different devices.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2022
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2022.3194124