基于高阶谱和时域分析的电台稳态特征提取算法
doi: 10.3724/SP.J.1146.2012.01227
Extraction Algorithm of Radio Steady State Characteristics Based on High Order Spectrum and Time-domain Analysis
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摘要: 该文针对稳态条件下通信电台指纹特征的提取问题,提出一种基于高阶谱和时域分析的电台稳态特征提取算法。首先对电台的稳态工作状态进行数学建模,分析现有双谱特征提取算法的不足。进而充分利用矩形积分双谱的周期性,并结合时域分析提出一种改进的电台稳态特征提取算法,从理论上证明了该算法适用于任意阶的高阶谱特征提取。最后,通过实测数据验证了该算法的有效性和可靠性。与传统矩形双谱特征提取算法相比,该算法将识别正确率从90%提高到97%;在识别率相同的情况下,该算法的效率相比原算法有了很大提升。Abstract: A radio extraction algorithm of steady state based on the high order spectrum and time-domain analysis is presented for the radio fingerprint features extraction problem on the condition of steady-state operation. Firstly, the mathematical model of steady-state operation is constructed and the disadvantages of existing bispectrum feature extraction algorithm are analyzed. Secondly, combining the periodicity of rectangular integral bispectrum with the time-domain analysis, a modified radio extraction algorithm of steady state is proposed, whose applicability for any kind of high order spectral features extraction is also proved. Finally, the results of computation experiment with measured data verify the good efficiency and reliability of the proposed algorithm. By comparison with the traditional rectangular integral bispectrum algorithm, the proposed algorithm improves the accuracy rate from 90% to 97%. Moreover, in the case of the same accuracy rate, the proposed algorithm obtains a higher efficiency than the traditional one.
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