本文關(guān)鍵詞： 輻射源信號(hào)指紋識(shí)別 相位噪聲 載頻估計(jì) 雜散特征 高階譜特征　出處：《電子科技大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：輻射源指紋識(shí)別技術(shù)是信號(hào)處理學(xué)科中一門新興的研究方向。因此,本文通過(guò)對(duì)通信信號(hào)輻射源的個(gè)體細(xì)微特征進(jìn)行分析與提取,并利用這些特征進(jìn)行分類識(shí)別技術(shù)進(jìn)行了研究。本文的主要工作包括以下3個(gè)方面:1.研究了基于碼速率和載頻特征提取技術(shù),改進(jìn)了相位差分載頻估計(jì)算法,利用前后向相位差分方法,對(duì)噪聲相位增量做兩次平滑處理,降低了相位噪聲對(duì)載頻估計(jì)的影響,提高了估計(jì)精度。并根據(jù)Haar小波變換法與短時(shí)傅立葉變換法的時(shí)頻能量對(duì)碼速率估計(jì)方法進(jìn)行了研究。理論分析與仿真實(shí)驗(yàn)表明,本文的碼速率和載頻估計(jì)精度能夠滿足對(duì)截獲的電臺(tái)信號(hào)載頻特征提取的要求。2.研究了輻射源包絡(luò)信息雜散特征的分析與提取技術(shù)。給出了Hilbert變換法、Teager-Kaiser法以及基于信號(hào)正交分量重構(gòu)的包絡(luò)提取算法;研究了信號(hào)包絡(luò)的R與J特征、描述分形集的復(fù)雜性和不規(guī)則性的盒維數(shù)特征、描述分形集在區(qū)域空間上的分布疏密的信息維數(shù)特征以及描述信號(hào)包絡(luò)變化規(guī)律的Lempel-Ziv復(fù)雜度特征等包絡(luò)調(diào)制特征提取與分析方法。然后利用截獲信號(hào)的Hilbert邊緣譜譜對(duì)稱特性和Hilbert Huang變換時(shí)頻分布灰度圖像提取信號(hào)的指紋特征。實(shí)驗(yàn)表明不同信號(hào)頻譜對(duì)稱性特征向量間的差別較大,聚類效果較好,適用于識(shí)別分類不同的輻射源信號(hào)。3.研究了基于高階譜的信號(hào)指紋分析與提取。通過(guò)對(duì)四種局部雙譜,以及矩形積分雙譜等基于高階譜的信號(hào)指紋特征提取方法,并利用Fisher鑒別函數(shù)仿真驗(yàn)證了這些雙譜分析方法在信號(hào)特征提取方面的性能。實(shí)驗(yàn)表明,矩形積分雙譜相較局部雙譜分析方法,在提取信號(hào)個(gè)體特征方面的性能較好。
[Abstract]:The fingerprint identification of emitter is a new research direction in the field of signal processing. Therefore, this paper analyzes and extracts the individual fine features of the emitter of communication signal. The main work of this paper includes the following three aspects: 1.The technology based on code rate and carrier frequency feature extraction is studied, and the phase difference carrier frequency estimation algorithm is improved. The phase increment of noise is smoothed twice by the method of forward and backward phase difference, and the influence of phase noise on carrier frequency estimation is reduced. The estimation accuracy is improved. The method of code rate estimation based on Haar wavelet transform and short time Fourier transform is studied. The theoretical analysis and simulation results show that, The code rate and carrier frequency estimation accuracy of this paper can meet the requirements of carrier frequency feature extraction of intercepted radio signals. 2. The analysis and extraction techniques of stray features of emitter envelope information are studied. The Hilbert transform method and the base method are given. The envelope extraction algorithm based on orthogonal component reconstruction; The R and J characteristics of the signal envelope are studied, and the box dimension features of the complexity and irregularity of the fractal set are described. The method of extracting and analyzing the information dimension features of fractal set and the Lempel-Ziv complexity feature describing the variation of signal envelope is presented. Then, the Hilbert edge spectrum of intercepted signal is used. Spectral symmetry and fingerprint feature extracted from time-frequency gray-scale image of Hilbert Huang transform show that the difference of spectrum symmetry characteristic vectors between different signals is great. The clustering effect is good, which is suitable for the recognition of emitter signals with different classification. The fingerprint analysis and extraction of signals based on high order spectrum are studied. As well as rectangle integral bispectrum and other signal fingerprint feature extraction methods based on high order spectrum. The simulation of Fisher discriminant function is used to verify the performance of these bispectral analysis methods in signal feature extraction. The experimental results show that, Compared with the local bispectrum analysis method, the rectangular integral bispectrum has better performance in extracting individual features of signals.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN911.7

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本文編號(hào)：1504998