| 一种基于ST-RFT算法的数字调制信号识别方法 |
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| 引用本文： | 刘丹,马秀荣,单云龙.一种基于ST-RFT算法的数字调制信号识别方法[J].计算机科学,2018,45(5):64-68. |
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| 作者姓名： | 刘丹 马秀荣 单云龙 |
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| 作者单位： | 天津理工大学计算机与通信工程学院 天津300384,天津理工大学计算机与通信工程学院 天津300384,天津理工大学计算机与通信工程学院 天津300384 |
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| 基金项目： | 本文受天津市科学技术委员会项目:天津市应用基础与前沿技术研究计划项目(15JCQNJC01100)资助 |
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| 摘 要： | 将短时拉曼努金傅里叶变换(ST-RFT)应用于数字调制信号识别的研究中,以寻求提高低SNR条件下数字调制信号识别率的新方法。通过归一化ST-RFT谱图计算、特征参量提取以及阈值判别来实现调制信号的识别。针对5种常见的数字调制信号进行仿真分析,结果表明,在SNR=0 dB的信噪比条件下,基于ST-RFT算法的数字调制信号识别方法的平均识别率可以达到90%,比基于谱图时频分析法的识别率提高了10.4%；特别是相比于基于瞬时幅度和瞬时频率的特征方法,4FSK调制信号的识别率可提高9%。基于ST-RFT算法的数字调制信号识别方法能够 在低SNR条件下有效识别数字调制信号,具有良好的工作性能。
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| 关 键 词： | 数字调制信号识别 短时拉曼努金傅里叶变换 特征参数 识别率 |
| 收稿时间： | 2017/2/10 0:00:00 |
| 修稿时间： | 2017/4/28 0:00:00 |
Digital Modulation Signal Recognition Method Based on ST-RFT Algorithm |
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| LIU Dan,MA Xiu-rong and SHAN Yun-long.Digital Modulation Signal Recognition Method Based on ST-RFT Algorithm[J].Computer Science,2018,45(5):64-68. |
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| Authors: | LIU Dan MA Xiu-rong and SHAN Yun-long |
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| Affiliation: | School of Computer and Communication Engineering,Tianjin University of Technology,Tianjin 300384,China,School of Computer and Communication Engineering,Tianjin University of Technology,Tianjin 300384,China and School of Computer and Communication Engineering,Tianjin University of Technology,Tianjin 300384,China |
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| Abstract: | In this paper,the short-time Ramanujan Fourier transform(ST-RFT) algorithm was applied in the research of modulation signal recognition to obtain a new method which can improve the correct recognition rate in low signal-to-noise ratio(SNR) environment.The modulation signals recognition was achieved by normalized ST-RFT spectrogram calculation,characteristic parameters extraction and threshold decision.The simulation results show that when SNR is 0 dB,the average correct recognition rate of the method based on ST-RFT algorithm can reach 90%,which is increased by 10.4% compared with that based on spectrogram time-frequency analysis algorithm.Especially,the correct recognition rate of the proposed method for 4FSK signal can increased by 9% compared with that of the method based on instantaneous amplitude and instantaneous frequency features.The effectiveness and reliability of the proposed method in low SNR are proved by simulation results. |
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| Keywords: | Digital modulation signal recognition Short-time Ramanujan Fourier transform Characteristic parameters Recognition rate |
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