本文關(guān)鍵詞： 調(diào)制識別 特征提取 高階累積量 瞬時特征 LabVIEW　出處：《北京郵電大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：為了在當(dāng)前復(fù)雜的通信環(huán)境中更加有效和可靠地進行信息傳輸,多種信號調(diào)制技術(shù)被應(yīng)用到通信系統(tǒng)中。與此同時,信號調(diào)制識別技術(shù)在軍用和民用領(lǐng)域的應(yīng)用逐漸引起人們的重視,如何有效地識別信號的調(diào)制方式也越來越受到人們的關(guān)注。為了彌補只基于高階累積量或信號瞬時特征等單一信號調(diào)制識別算法的不足,本文在調(diào)制信號特征參數(shù)提取和分類識別研究的基礎(chǔ)上,提出了基于高階累積量與信號瞬時特征的特征參數(shù)提取方法,并根據(jù)獲得的特征參數(shù),提出了性能良好的基于決策樹的調(diào)制信號分類識別方法。此外,設(shè)計實現(xiàn)了基于LabVIEW的信號調(diào)制識別系統(tǒng),將提出的信號調(diào)制識別算法很好地應(yīng)用到了實際工程中。 本文的主要工作包括： 1.詳細分析了信號的調(diào)制原理,包括模擬調(diào)制與數(shù)字調(diào)制,并給出了相應(yīng)的調(diào)制信號時域和頻域波形以及特性介紹。重點研究了AM、2ASK、4ASK、2FSK、4FSK、8FSK、2PSK、4PSK、16QAM九種模擬、數(shù)字信號理想情況下及信噪比為5dB情況下的時域波形。 2.研究了信號調(diào)制識別中的特征參數(shù)提取和分類識別等關(guān)鍵技術(shù)。提出了基于高階累積量與信號瞬時特征的特征參數(shù)提取方法,利用決策樹分類器,提出了基于決策樹的調(diào)制信號分類識別方法并進行了仿真實驗。實驗結(jié)果表明,本文提出的信號調(diào)制識別算法設(shè)計簡單,可以有效地識別AM、2ASK、4ASK、2FSK、4FSK、8FSK、2PSK、4PSK、16QAM九種模擬、數(shù)字信號。 3.研究了基于LabVIEW的系統(tǒng)開發(fā)的關(guān)鍵技術(shù),在提出的信號調(diào)制識別算法的基礎(chǔ)上,設(shè)計實現(xiàn)了基于LabVIEW的信號調(diào)制識別系統(tǒng),并進行了系統(tǒng)的搭建與驗證。驗證結(jié)果表明系統(tǒng)運行準(zhǔn)確,從而證明了本文提出的信號調(diào)制識別算法的正確性以及算法應(yīng)用到實際工程中的有效性。
[Abstract]:In the current complex communication environment is more effective and reliable transmission of information, a variety of signal modulation technique is applied to the communication system. At the same time, the signal modulation recognition technology has gradually attracted people's attention in the field of military and civilian applications, how to effectively identify the signal modulation is also more and more attention to. Make up only based on lack of high order cumulant or signal instantaneous characteristics of single signal modulation recognition algorithm, based on the characteristics of modulation signal parameter extraction and classification research, proposed characteristic parameters extraction methods of high order cumulant and instantaneous feature based, and according to the characteristic parameters of the proposed performance classification signal modulation method based on decision tree good. In addition, the design and implementation of signal modulation recognition system based on LabVIEW, the signal transfer The algorithm of system recognition is well applied to practical engineering.
The main work of this article includes:
1. a detailed analysis of the principle of modulation signal, including analog modulation and digital modulation, and gives the corresponding modulation signal in time domain and frequency domain waveform characteristics and introduction. We focus on AM, 2ASK, 4ASK, 2FSK, 4FSK, 8FSK, 2PSK, 4PSK, 16QAM nine kinds of analog, digital signal to noise and circumstances for the case of 5dB than the time-domain waveform.
The 2. key technology of signal modulation recognition in feature extraction and classification. We propose a feature extraction method of parameters of high order cumulant and instantaneous characteristics based on using decision tree classifier, proposed modulation signal classification method based on decision tree and simulation experiment. The experimental results show that the design of signal modulation recognition algorithm is proposed in this paper is simple, can effectively identify AM, 2ASK, 4ASK, 2FSK, 4FSK, 8FSK, 2PSK, 4PSK, 16QAM nine kinds of analog, digital signal.
3. research on the key technology of system development based on LabVIEW, based on the signal modulation recognition algorithm is proposed on the design and implementation of signal modulation recognition system based on LabVIEW, and the construction and verification system. The verification results show that the system works accurately, which proves the signal modulation recognition algorithm is proposed in this paper is correct and the algorithm is applied to the effectiveness in practical projects.

【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN911.3

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