数字信号调制方式的识别技术研究

发布时间：2018-01-06 03:28

本文关键词：数字信号调制方式的识别技术研究　出处：《河北大学》2017年硕士论文　论文类型：学位论文

【摘要】：为了在信号密集和有噪声干扰的环境下判断出接收信号的调制方式,通常使用调制识别技术。调制识别技术在民用和军事无线通信中的信号监测、信息截获、干扰识别和电子对抗等方面有着广泛的应用,是认知无线电、频谱感知等领域研究的基础,因此这一技术的研究从未间断并越来越受到人们的重视。本文在前人工作的基础上,对数字通信信号的调制识别技术进行了研究和探索,取得的主要成果和创新点有:(1)针对四种数字调制信号MASK、MFSK、MPSK和MQAM识别问题,根据归一化前后调制信号的小波变换包络之间的差异性,提出基于小波变异系数差值和小波相似度特征的识别方法。首先在不同小波尺度下,采用小波变异系数差值和小波相似度作为MASK、MFSK、MPSK和MQAM信号类间识别的特征参数;然后在调制信号的类内识别中,分别采用高阶累积量值和未归一化小波变换包络的标准差值作为特征参数实现对调制信号的识别。该方法特征复杂度低,参数容错性强,在较低信噪比环境下有较好的识别效率。(2)针对单通道时频域混叠信号环境下难以处理的信号调制识别问题,研究了一种将高阶累积量与循环矩相结合的识别方法。首先对混叠信号的高阶累积量特征进行分析;然后引入循环矩特征增加高阶累积量特征的识别范围;最后联合两种识别特征利用基于结构风险最小化准则的支持向量机(Support Vector Machines,SVM)对混叠信号调制方式进行有效的识别。该方法鲁棒性强,保持较少特征参数的同时能够识别较多的信号类型。
[Abstract]:In order to judge the modulation mode of the received signal in the environment of dense signal and noise interference, the modulation identification technology is usually used. The modulation identification technology is used to monitor the signal and intercept the information in the civil and military wireless communication. Interference recognition and electronic countermeasures are widely used, which is the basis of cognitive radio, spectrum sensing and other fields. Therefore, the research of this technology has never stopped and has been paid more and more attention. Based on the previous work, the modulation recognition technology of digital communication signal is studied and explored in this paper. The main achievements and innovations are: (1) aiming at four kinds of digital modulation signal MASK / MFSKMPSK and MQAM recognition problems. According to the difference between wavelet transform envelopes of modulated signals before and after normalization, a method based on wavelet variation coefficient difference and wavelet similarity features is proposed. Firstly, under different wavelet scales. Wavelet variation coefficient difference and wavelet similarity are used as feature parameters for recognition between MASK MFSKMPSK and MQAM signals. Then in the class recognition of modulation signal, the high order cumulant value and the standard difference value of the envelope of unnormalized wavelet transform are used as the characteristic parameters to realize the recognition of modulation signal respectively. The method has low feature complexity. Because of its strong fault tolerance and better recognition efficiency in low SNR environment, it is difficult to deal with the signal modulation recognition problem in single channel time-frequency domain aliasing signal environment. A recognition method combining high order cumulants with cyclic moments is studied. Firstly, the characteristics of high order cumulants of mixed signals are analyzed. Then the cyclic moment feature is introduced to increase the recognition range of higher order cumulant features. Finally, two recognition features are combined using support vector machine support Vector Machines based on structural risk minimization criterion. SVM) is an effective method to identify the modulation modes of aliasing signals, which is robust and can recognize more types of signals while keeping fewer characteristic parameters.
【学位授予单位】：河北大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN911.3

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