无线信号调制模式识别技术的研究
发布时间：2018-08-18 08:59
【摘要】：通信信号调制识别技术广泛地应用于军事、民用领域,其主要任务是在多信号环境下识别出截获信号的调制类型,给出相应的调制参数,为后续信号处理和分析提供先验信息。调制识别尤其在无线电监测方面起着基础且至关重要的作用。近年来,调制模式识别成为国内外的研究热点,涌现了大量不同类型的新型识别算法。然而,目前大部分调制识别算法主要停留在理论研究与仿真实现阶段。在真实的传播环境条件下,这些算法通常具有较差的性能,因而很难应用于实际的无线电监测工作中。为此,本文重点关注调制识别方法的实际应用。在对日常无线电监测中九种典型的超短波信号识别深入研究的基础之上,本文提出了一种较为精确、稳定性高的超短波信号识别方案,并开发了相应的识别软件,实现了对真实采集信号的识别分析。论文主要内容如下： 首先,介绍了调制识别技术的研究背景和现状。从通信信号调制类型入手,介绍了常见模拟调制信号(DSB、FM)和数字调制信号(MASK、MFSK、MPSK)的基本原理和特性,并利用MATLAB对各种信号进行了建模仿真。 其次,对基本的识别统计量进行了分析,并利用MATLAB对各个识别统计量进行了建模仿真,得到了识别统计量的判决门限。基于决策理论设计了2ASK、 BPSK、4ASK、QPSK、2FSK、4FSK、16QAM七种信号的识别算法。在信噪比为7.8dB时,识别成功率已经达到97%以上。 然后,基于ITU-RSM.1600建议书,对信号存在性及波特率、载波频率、发射带宽等参数估计方法进行分析,提出了信号平方谱、谱相关、基于Haar小波变换三种新的波特率估计方法,并通过大量MATLAB仿真实验,验证新方法的适用性。 最后,重点研究了BPSK、QPSK、8PSK、OQPSK、π/4DQPSK、FSK、4FSK,16QAM、32QAM九种典型超短波信号的调制方式识别。基于超短波信号的特点,研究了一种新的基于MATLAB的调制方式识别系统方案,并取得到了良好的识别性能,该套方案能够在超短波日常监测中得到初步应用。
[Abstract]:Communication signal modulation recognition technology is widely used in military and civil fields. Its main task is to identify the modulation types of intercepted signals in multi-signal environment, and to provide corresponding modulation parameters, which can provide prior information for subsequent signal processing and analysis. Modulation recognition plays a fundamental and crucial role in radio monitoring. In recent years, modulation pattern recognition has become a hot topic at home and abroad, and a large number of new recognition algorithms of different types have emerged. However, at present, most of the modulation recognition algorithms are mainly in the stage of theoretical research and simulation. In real transmission environment, these algorithms usually have poor performance, so they are difficult to be applied to actual radio monitoring. Therefore, this paper focuses on the practical application of modulation recognition method. Based on the in-depth study of nine typical ultrashort wave signals in daily radio monitoring, this paper presents a more accurate and stable scheme for recognition of ultrashort wave signals, and develops the corresponding recognition software. The recognition and analysis of the real collected signals are realized. The main contents of this paper are as follows: firstly, the research background and present situation of modulation recognition technology are introduced. Based on the modulation types of communication signals, this paper introduces the basic principles and characteristics of common analog modulation signals (DSB-FM) and digital modulated signals (MASK / MFSKK / MPSK), and uses MATLAB to model and simulate various signals. Secondly, the basic identification statistics are analyzed, and each recognition statistic is modeled and simulated by MATLAB, and the decision threshold of recognition statistics is obtained. Based on the decision theory, seven signal recognition algorithms, 2ASK, BPSKO 4ASK, 2FSK4FSK4FSK4FSK16QAM, are designed. When the SNR is 7.8dB, the success rate of recognition is over 97%. Then, based on the ITU-RSM.1600 recommendation, we analyze the signal existence, baud rate, carrier frequency, transmission bandwidth and other parameter estimation methods, and propose three new baud rate estimation methods based on Haar wavelet transform, such as signal squared spectrum, spectral correlation, and Haar wavelet transform. The applicability of the new method is verified by a large number of MATLAB simulation experiments. Finally, the modulation mode recognition of nine typical ultrashort wave signals (OQPSK, 蟺 / 4DQPSK / FSK4FSK4FSK4QAM16QAM32QAM) is studied. Based on the characteristics of ultrashort wave signal, a new scheme of modulation recognition system based on MATLAB is studied, and a good recognition performance is obtained. The scheme can be applied in daily monitoring of ultrashort wave.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.3
[Abstract]:Communication signal modulation recognition technology is widely used in military and civil fields. Its main task is to identify the modulation types of intercepted signals in multi-signal environment, and to provide corresponding modulation parameters, which can provide prior information for subsequent signal processing and analysis. Modulation recognition plays a fundamental and crucial role in radio monitoring. In recent years, modulation pattern recognition has become a hot topic at home and abroad, and a large number of new recognition algorithms of different types have emerged. However, at present, most of the modulation recognition algorithms are mainly in the stage of theoretical research and simulation. In real transmission environment, these algorithms usually have poor performance, so they are difficult to be applied to actual radio monitoring. Therefore, this paper focuses on the practical application of modulation recognition method. Based on the in-depth study of nine typical ultrashort wave signals in daily radio monitoring, this paper presents a more accurate and stable scheme for recognition of ultrashort wave signals, and develops the corresponding recognition software. The recognition and analysis of the real collected signals are realized. The main contents of this paper are as follows: firstly, the research background and present situation of modulation recognition technology are introduced. Based on the modulation types of communication signals, this paper introduces the basic principles and characteristics of common analog modulation signals (DSB-FM) and digital modulated signals (MASK / MFSKK / MPSK), and uses MATLAB to model and simulate various signals. Secondly, the basic identification statistics are analyzed, and each recognition statistic is modeled and simulated by MATLAB, and the decision threshold of recognition statistics is obtained. Based on the decision theory, seven signal recognition algorithms, 2ASK, BPSKO 4ASK, 2FSK4FSK4FSK4FSK16QAM, are designed. When the SNR is 7.8dB, the success rate of recognition is over 97%. Then, based on the ITU-RSM.1600 recommendation, we analyze the signal existence, baud rate, carrier frequency, transmission bandwidth and other parameter estimation methods, and propose three new baud rate estimation methods based on Haar wavelet transform, such as signal squared spectrum, spectral correlation, and Haar wavelet transform. The applicability of the new method is verified by a large number of MATLAB simulation experiments. Finally, the modulation mode recognition of nine typical ultrashort wave signals (OQPSK, 蟺 / 4DQPSK / FSK4FSK4FSK4QAM16QAM32QAM) is studied. Based on the characteristics of ultrashort wave signal, a new scheme of modulation recognition system based on MATLAB is studied, and a good recognition performance is obtained. The scheme can be applied in daily monitoring of ultrashort wave.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.3
【参考文献】
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