稳定分布噪声下通信信号的参数估计及调制识别
发布时间：2018-09-18 18:31
【摘要】：通信信号的参数估计和调制识别是非合作通信系统中一项关键的技术,在电子侦察、无线电频谱监测、紧急救援、物联网工程等领域应用中有着重要的作用。调制识别是指在不知道调制具体信息的情形下,直接从接收信号中估计出发送信号调制类型和某些参数信息,为信号解调、威胁评估、干扰识别等后续信号分析和处理过程提供依据,而参数估计是调制方式识别和信号盲解调等处理的必要前提。同时随着应用场景的不断变化,信道常常会出现一些显著的非高斯脉冲噪声,采用高斯模型设计的信号处理系统将会失效。经过学者研究论证,发现用稳定分布描述生活中广泛存在的脉冲噪声更加有效,因此研究稳定分布噪声环境下通信信号的参数估计及调制识别问题更加具有实际的工程意义。本文主要对稳定分布噪声环境下通信信号的参数估计和调制识别算法进行了研究。(1)针对稳定分布噪声环境下传统循环谱算法估计通信信号参数失效的问题,本文基于传统循环谱参数估计算法,通过构造非线性变换的方法对广义循环谱进行了定义,利用广义循环谱截面谱线的位置对通信信号的载波频率和码元速率进行了联合估计,并以BPSK信号为例对算法进行了理论验证,最后对BPSK和16QAM信号进行了实验仿真验证。(2)针对稳定分布噪声环境下高阶累积量不能对通信信号进行识别的问题,本文定义了广义高阶累积量,通过分析各个信号各阶广义高阶累积量,构造出特征参数用来对MFSK和MPSK信号进行类间识别,然后分析BPSK和QPSK、2FSK和4FSK信号的广义循环谱截面谱线的特点,利用这些特点对其分别进行类内识别,并设计出了分类器。最后通过实验对2FSK、4FSK、BPSK和QPSK信号的类间和类内识别进行了仿真验证。
[Abstract]:The parameter estimation and modulation identification of communication signals is a key technology in non-cooperative communication systems, which plays an important role in the applications of electronic reconnaissance, radio spectrum monitoring, emergency rescue, Internet of things engineering and so on. Modulation identification is to estimate the modulation type and some parameter information of the transmitted signal directly from the received signal without knowing the specific information of the modulation, so as to demodulate the signal and evaluate the threat. The analysis and processing of subsequent signals such as interference identification provide the basis, and parameter estimation is a necessary prerequisite for modulation identification and blind demodulation. At the same time, with the continuous change of the application scene, some prominent non-Gao Si impulse noise often appears in the channel, and the signal processing system designed by the Gao Si model will fail. Through the research and demonstration of scholars, it is found that it is more effective to describe the pulse noise widely existing in life by using stable distribution, so it is more important to study the parameter estimation and modulation identification of communication signal under stable distribution noise. This paper mainly studies the parameter estimation and modulation identification algorithm of communication signal under stable distributed noise environment. (1) aiming at the problem of estimating communication signal parameter failure by traditional cyclic spectrum algorithm under stable distributed noise environment. Based on the traditional cyclic spectrum parameter estimation algorithm, the generalized cyclic spectrum is defined by constructing nonlinear transformation, and the carrier frequency and symbol rate of the communication signal are estimated by using the position of the cross section line of the generalized cyclic spectrum. Taking the BPSK signal as an example, the algorithm is theoretically verified. Finally, the experimental simulation of BPSK and 16QAM signals is carried out. (2) aiming at the problem that the high-order cumulant can not recognize the communication signal in the environment of stable distributed noise, In this paper, the generalized high-order cumulant is defined. By analyzing the generalized high-order cumulants of each signal, the characteristic parameters are constructed for the inter-class identification of MFSK and MPSK signals. Then, the characteristics of the generalized cyclic spectral cross section lines of BPSK, QPSK,2FSK and 4FSK signals are analyzed, which are used to identify them in class, and a classifier is designed. Finally, the inter-class and intra-class recognition of 2FSK4FSKK and QPSK signals are verified by simulation.
【学位授予单位】：兰州理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN911
[Abstract]:The parameter estimation and modulation identification of communication signals is a key technology in non-cooperative communication systems, which plays an important role in the applications of electronic reconnaissance, radio spectrum monitoring, emergency rescue, Internet of things engineering and so on. Modulation identification is to estimate the modulation type and some parameter information of the transmitted signal directly from the received signal without knowing the specific information of the modulation, so as to demodulate the signal and evaluate the threat. The analysis and processing of subsequent signals such as interference identification provide the basis, and parameter estimation is a necessary prerequisite for modulation identification and blind demodulation. At the same time, with the continuous change of the application scene, some prominent non-Gao Si impulse noise often appears in the channel, and the signal processing system designed by the Gao Si model will fail. Through the research and demonstration of scholars, it is found that it is more effective to describe the pulse noise widely existing in life by using stable distribution, so it is more important to study the parameter estimation and modulation identification of communication signal under stable distribution noise. This paper mainly studies the parameter estimation and modulation identification algorithm of communication signal under stable distributed noise environment. (1) aiming at the problem of estimating communication signal parameter failure by traditional cyclic spectrum algorithm under stable distributed noise environment. Based on the traditional cyclic spectrum parameter estimation algorithm, the generalized cyclic spectrum is defined by constructing nonlinear transformation, and the carrier frequency and symbol rate of the communication signal are estimated by using the position of the cross section line of the generalized cyclic spectrum. Taking the BPSK signal as an example, the algorithm is theoretically verified. Finally, the experimental simulation of BPSK and 16QAM signals is carried out. (2) aiming at the problem that the high-order cumulant can not recognize the communication signal in the environment of stable distributed noise, In this paper, the generalized high-order cumulant is defined. By analyzing the generalized high-order cumulants of each signal, the characteristic parameters are constructed for the inter-class identification of MFSK and MPSK signals. Then, the characteristics of the generalized cyclic spectral cross section lines of BPSK, QPSK,2FSK and 4FSK signals are analyzed, which are used to identify them in class, and a classifier is designed. Finally, the inter-class and intra-class recognition of 2FSK4FSKK and QPSK signals are verified by simulation.
【学位授予单位】：兰州理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN911
【参考文献】
相关期刊论文 前10条
1 胡君朋;黄芝平;刘纯武;苏绍t，
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