本文關(guān)鍵詞： 調(diào)制識別 特征提取 小波變換 高階累積量　出處：《長春理工大學》2016年碩士論文　論文類型：學位論文

【摘要】：在現(xiàn)代通信技術(shù)中,通信信號的制式識別在電子對抗、頻譜管理、自適應(yīng)接收、認知無線電等多個領(lǐng)域有廣泛的應(yīng)用。在現(xiàn)有的文獻中,通信信號的調(diào)制制式識別方法主要分為兩種:基于決策理論的最大似然假設(shè)檢驗方法和基于特征提取的模式識別方法。第一種方法能夠達到很好的識別效果,但是計算復雜,而且對頻偏、相偏、定時誤差等非常敏感。相比較而言,第二種方法計算復雜度低,效率高,在特征選取合理的時候能夠達到很好的識別效果,且具有較高的穩(wěn)定性。因此本文重點研究基于特征提取的模式識別方法。本文應(yīng)用小波變換方法,對PSK、ASK、FSK信號提取了特征參量并對信號進行了有效的分類。在假定噪聲為加性高斯白噪聲的條件下建立了信號模型,說明了尺度因子的選取問題,通過計算小波變換系數(shù)幅值提取了信號的特征參數(shù)。通過MATLAB對通信信號進行了仿真,說明了算法的有效性。本文應(yīng)用高階累積量,針對多徑信道條件,對BPSK信號和QPSK信號的制式識別進行了較深入研究。在無線通信中,實際信道通常有多徑衰落現(xiàn)象。在這種情況下,建立在高斯白噪聲信道模型上的調(diào)制識別算法的性能通常會下降甚至失效。針對此問題,提出了基于四階累積量和六階累積量相結(jié)合的調(diào)制識別算法。多徑數(shù)目為2時,從理論上證明了該算法和基于四階累積量的算法相比,能夠更好的抗多徑干擾。仿真結(jié)果表明,在多徑衰落條件下,該算法對BPSK信號和QPSK信號的識別率高于基于四階累積量的算法。在信噪比為2dB的多徑衰落信道情況下,分類BPSK和QPSK信號的識別率幾乎達到100%;在識別BPSK信號時,此算法性能明顯優(yōu)于基于四階累積量的算法。
[Abstract]:In modern communication technology, communication signal recognition has been widely used in many fields, such as electronic countermeasure, spectrum management, adaptive reception, cognitive radio and so on. The modulation recognition method of communication signal is divided into two kinds: the maximum likelihood hypothesis test method based on decision theory and the pattern recognition method based on feature extraction. The first method can achieve good recognition effect. But the calculation is complex and sensitive to frequency offset, phase offset and timing error. Compared with other methods, the second method has low computational complexity and high efficiency, and can achieve a good recognition effect when the feature selection is reasonable. Therefore, this paper focuses on the research of pattern recognition based on feature extraction. In this paper, we apply wavelet transform method to PSK ask. The characteristic parameters of FSK signal are extracted and the signal is classified effectively. The signal model is established under the assumption that the noise is additive Gao Si white noise, which explains the selection of scale factor. The characteristic parameters of the signal are extracted by calculating the amplitude of the wavelet transform coefficient. The simulation of the communication signal by MATLAB shows the validity of the algorithm. In this paper, the high-order cumulant is applied. In view of the multipath channel condition, the standard recognition of BPSK signal and QPSK signal is deeply studied. In wireless communication, the actual channel usually has multipath fading phenomenon. In this case. The performance of modulation recognition algorithm based on Gao Si white noise channel model usually decreases or even fails. A modulation recognition algorithm based on the combination of fourth-order cumulant and sixth-order cumulant is proposed. The number of multipath is 2:00. It is proved theoretically that this algorithm is compared with the algorithm based on fourth-order cumulant. The simulation results show that under the condition of multipath fading, it can resist multipath interference better. The recognition rate of BPSK signal and QPSK signal is higher than that based on fourth-order cumulant. In the case of a 2dB signal-to-noise ratio (SNR) multipath fading channel. The recognition rate of classified BPSK and QPSK signals is almost 100. The performance of this algorithm is better than that based on fourth order cumulant in the recognition of BPSK signals.
【學位授予單位】：長春理工大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TN911.3
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本文編號：1444208