| 一种改进的数字信号自动识别方法 |
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| 引用本文： | 李俊俊,陆明泉,冯振明.一种改进的数字信号自动识别方法[J].系统工程与电子技术,2005,27(12):2023-2024. |
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| 作者姓名： | 李俊俊 陆明泉 冯振明 |
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| 作者单位： | 清华大学电子工程系,北京,100084 |
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| 摘 要： | 现有数字信号自动调制识别方法大多只适用于无记忆信号,如PSK、ASK、FSK信号等。将有记忆信号(MSK信号)和无记忆信号一起考虑,提出了一种改进的数字信号自动识别方法。该方法采用信号的瞬时统计量作为特征参数,采用多层神经网络作为分类器。计算机仿真表明:当噪声采用高斯白噪声,并且信噪比大于15dB时,识别率高于96%;当信噪比不低于10dB时,识别率不低于90%。
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| 关 键 词： | 调制识别 特征提取 多层神经网络 分类器 |
| 文章编号： | 1001-506X(2005)12-2023-02 |
| 修稿时间： | 2004年11月15 |
Modified automatic digital modulation recognition algorithm |
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| LI Jun-jun,LU Ming-quan,FENG Zhen-ming.Modified automatic digital modulation recognition algorithm[J].System Engineering and Electronics,2005,27(12):2023-2024. |
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| Authors: | LI Jun-jun LU Ming-quan FENG Zhen-ming |
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| Abstract: | WT9.BZ]In the past, most digital modulation recognition algorithms focused on only memoryless signals, such as PSK, ASK, FSK. A modified algorithm is presented with MSK signals added to the existing set of signals that can be recognized. The method uses simultaneous statistical moments of received signals as their features and uses multi-layer perceptron (MLP) as classifiers. The algorithm's performance has been evaluated by simulating different types of band-limited digital signals corrupted by white Gaussian noise. It is found that the overall success rate is over 96% at the signal to noise ratio (SNR) of 15 dB. Furthermore, when the signal to noise ratio(SNR) is over 10 dB, the overall success rate is not lower than 90% . |
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| Keywords: | modulation recognition feature extraction multi-layer perceptron classifier |
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