基于成分分析的射频干扰源个体识别

Individual Identification of the Radio Frequency Interference Sources Based on Component Analysis

射频干扰源个体识别在军事领域有重要的应用价值,相关的研究成果较少。从分析射频干扰源稳态信号的各种成分出发,提出了基于成分分析的射频干扰源个体识别方法。该方法首先对干扰源稳态信号进行成分分离和恢复,然后选取最能反映个体差异的若干个次成分进行特征降维和识别。通过实测数据实验证明了该方法的识别效果,并和现有的基于经验模态分解的个体识别方法进行了比较。结果表明该方法要优于现有的方法,并且受信噪比影响较小,在5 d B^20 d B的信噪比范围内识别率在80%以上。

The individual identification of radio frequency interference sources has important application value in the military field,but the related research is few. Individual identification method of the radio frequency interference sources based on component analysis is proposed through analyzing the various components of the stable signal of radio frequency interference emitter in this paper. Firstly,the various components of the stable signal of interference sources are separated and recovered,then the subordinate components that can make the individual differences obvious are selected for feature dimension reduction and identification in the proposed method. The real data experiment has shown the identification result of the proposed method comparing with the existing method based on empirical mode decomposition. The result has shown that the proposed method is superior to the existing method,and is not sensitive to the signal-to-noise ratio（ SNR） with the recognition rate over 80% in the SNR range of 5 dB ~ 20 dB.