無(wú)線信號(hào)調(diào)制模式識(shí)別技術(shù)的研究
發(fā)布時(shí)間：2018-08-18 08:59
【摘要】：通信信號(hào)調(diào)制識(shí)別技術(shù)廣泛地應(yīng)用于軍事、民用領(lǐng)域,其主要任務(wù)是在多信號(hào)環(huán)境下識(shí)別出截獲信號(hào)的調(diào)制類型,給出相應(yīng)的調(diào)制參數(shù),為后續(xù)信號(hào)處理和分析提供先驗(yàn)信息。調(diào)制識(shí)別尤其在無(wú)線電監(jiān)測(cè)方面起著基礎(chǔ)且至關(guān)重要的作用。近年來(lái),調(diào)制模式識(shí)別成為國(guó)內(nèi)外的研究熱點(diǎn),涌現(xiàn)了大量不同類型的新型識(shí)別算法。然而,目前大部分調(diào)制識(shí)別算法主要停留在理論研究與仿真實(shí)現(xiàn)階段。在真實(shí)的傳播環(huán)境條件下,這些算法通常具有較差的性能,因而很難應(yīng)用于實(shí)際的無(wú)線電監(jiān)測(cè)工作中。為此,本文重點(diǎn)關(guān)注調(diào)制識(shí)別方法的實(shí)際應(yīng)用。在對(duì)日常無(wú)線電監(jiān)測(cè)中九種典型的超短波信號(hào)識(shí)別深入研究的基礎(chǔ)之上,本文提出了一種較為精確、穩(wěn)定性高的超短波信號(hào)識(shí)別方案,并開(kāi)發(fā)了相應(yīng)的識(shí)別軟件,實(shí)現(xiàn)了對(duì)真實(shí)采集信號(hào)的識(shí)別分析。論文主要內(nèi)容如下： 首先,介紹了調(diào)制識(shí)別技術(shù)的研究背景和現(xiàn)狀。從通信信號(hào)調(diào)制類型入手,介紹了常見(jiàn)模擬調(diào)制信號(hào)(DSB、FM)和數(shù)字調(diào)制信號(hào)(MASK、MFSK、MPSK)的基本原理和特性,并利用MATLAB對(duì)各種信號(hào)進(jìn)行了建模仿真。 其次,對(duì)基本的識(shí)別統(tǒng)計(jì)量進(jìn)行了分析,并利用MATLAB對(duì)各個(gè)識(shí)別統(tǒng)計(jì)量進(jìn)行了建模仿真,得到了識(shí)別統(tǒng)計(jì)量的判決門(mén)限。基于決策理論設(shè)計(jì)了2ASK、 BPSK、4ASK、QPSK、2FSK、4FSK、16QAM七種信號(hào)的識(shí)別算法。在信噪比為7.8dB時(shí),識(shí)別成功率已經(jīng)達(dá)到97%以上。 然后,基于ITU-RSM.1600建議書(shū),對(duì)信號(hào)存在性及波特率、載波頻率、發(fā)射帶寬等參數(shù)估計(jì)方法進(jìn)行分析,提出了信號(hào)平方譜、譜相關(guān)、基于Haar小波變換三種新的波特率估計(jì)方法,并通過(guò)大量MATLAB仿真實(shí)驗(yàn),驗(yàn)證新方法的適用性。 最后,重點(diǎn)研究了BPSK、QPSK、8PSK、OQPSK、π/4DQPSK、FSK、4FSK,16QAM、32QAM九種典型超短波信號(hào)的調(diào)制方式識(shí)別�；诔滩ㄐ盘�(hào)的特點(diǎn),研究了一種新的基于MATLAB的調(diào)制方式識(shí)別系統(tǒng)方案,并取得到了良好的識(shí)別性能,該套方案能夠在超短波日常監(jiān)測(cè)中得到初步應(yīng)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.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：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.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN911.3
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