Research on C-E Fingerprint Extraction of Emitter

Jiaying Yue, Liuyang Gao, Nae Zheng
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Abstract

Aiming at the problem of limited presentation ability and easy drift of results for a single feature, a joint fingerprint feature extraction algorithm based on the complexity and entropy of instantaneous parameter (C-E) is proposed. From the perspective of signal information integrity, this paper multi-extract the secondary features of instantaneous amplitude, frequency and phase, and obtain the box dimension, information dimension, information entropy, as well as the Hilbert envelope spectrum information entropy newly proposed in this paper. Finally, the features are fused into C-E features to identify the individual radiation source. Compared with single class features, the recognition rate of the joint features is greatly improved at little time cost. In simulation experiment, the accuracy increases by 15.2% and 19.7% than fractal dimension and entropy respectively. And features have good independence and noise resistance under different environments.
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发射器C-E指纹提取方法研究
针对单个特征表示能力有限、结果容易漂移的问题,提出了一种基于瞬时参数复杂度和熵的指纹特征联合提取算法。本文从信号信息完整性的角度出发,对瞬时幅值、频率和相位的二次特征进行多重提取,得到盒子维数、信息维数、信息熵以及本文新提出的希尔伯特包络谱信息熵。最后,将这些特征融合成C-E特征来识别单个辐射源。与单类特征相比,联合特征的识别率大大提高,且时间成本较低。在模拟实验中,与分形维数和熵相比,准确率分别提高了15.2%和19.7%。并且在不同环境下具有良好的独立性和抗噪声性。
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