【摘要】 研究了基于通信辐射源射频指纹(RFF)的同类型设备分类识别理论,通过提取通信信号的围线积分双谱值来作为设备个体识别的特征向量,使用支持向量机(SVM)分类器进行识别。构建辐射源识别系统,并使用实测信号进行仿真测试。结果显示该方法具有稳定的识别效果,且在信噪比(SNR)为-22dB时,系统可以达到接近90%的分类识别准确度。这说明本文提出的基于双谱的RFF提取方法有效。更多还原

【Abstract】 The classification and recognition theories of the same type of equipment based on the Radio Frequency Fingerprint(RFF) of the communication radiation source are studied. The integral bispectrum values of the communication signal are extracted as the feature vector of the device, and the Support Vector Machine(SVM) classifier is used for identification. After constructing a radiation source identification system, the measured signals are used for simulation testing. The simulation results show a stable recognition effect by using the proposed method, and the system can achieve nearly 90% classification recognition accuracy when the Signal to Noise Ratio(SNR) is -22 dB. This result validates the effectiveness of bispectrum-based RF fingerprint extraction method.更多还原