载频稳定度在射频指纹识别中的应用研究

Radio Frequency Fingerprinting Identification Based on Carrier Frequency Stability

射频指纹识别是利用辐射源射频特征唯一性对其个体身份进行识别的技术,具有广阔的军民用应用前景。针对传统射频指纹特征稳定度不高、难以工程实现的问题,提出了一种基于辐射源频率偏移和相位噪声等多维频域特性的射频指纹识别方法。该方法以ADS-B信号为例,利用统计原理对频率偏移和相位噪声特征进行量化处理,并利用贝叶斯分类方法对信号进行分类以实现辐射源个体身份的识别。通过半实物生成和实采ADS-B信号数据两种方式对提出的算法进行实验验证。实验结果表明,该方法能够对同型号的辐射源进行有效区分,对真实环境下4个目标的识别正确率达到93.5%。

Radio frequency fingerprinting is a technology that uses the uniqueness of the radio frequency characteristics of the radiation source to identify its individual identity, which has broad application prospects for military and civilian applications. Aiming at the problem that the traditional RF fingerprint features were not stable and difficult to implement, a radio frequency fingerprint identification method based on multi-dimensional frequency domain characteristics such as radiation source frequency offset and phase noise was proposed. Taking the ADS-B signal as an example, statistical principles were utilized to quantify frequency offset and phase noise characteristics, and the Bayesian classification method was applied to classify the signals to finally realize the identification of the individual identity. The algorithm was validated by semi-physical generation and real-time ADS-B signal data. The experimental results showed that the method could effectively distinguish the same type of radiation source, and the recognition rate of the four targets in the real environment was 93.5%.