基于离散傅里叶变换的频移键控信号分类

Z. Yu, Y.Q. Shi, W. Su
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引用次数: 34

摘要

现有的基于决策理论的多频移键控(MFSK)信号分类器都假定对传输的MFSK信号参数有一定的先验知识;而基于特征的分类器存在一些局限性,如阈值依赖于信噪比(snr)。本文研究了MFSK信号振幅谱的一些有用性质。利用这些特性作为分类准则,开发了一种基于傅立叶变换的MFSK信号快速分类器。FFTC算法是实用的,因为它只需要对接收信号有一些合理的了解。结果表明,当信噪比>0dB时,FFTC算法对2-FSK、4-FSK、8-FSK、16-FSK和32-FSK信号的分类效果良好。FFTC算法还能很好地估计接收到的MFSK信号的频率偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
M-ary frequency shift keying signal classification based-on discrete Fourier transform
The existing decision-theory based classifiers for M-ary frequency shift keying (MFSK) signals have assumed that there is some prior knowledge of the transmitted MFSK signal parameters; while the feature-based classifiers have some limitations such as that their thresholds are signal-to-noise-ratio-dependent (SNR-dependent). In this paper, we investigate some useful properties of the amplitude spectrum of MFSK signals. Using these properties as classification criteria, a fast Fourier transform based classifier (FFTC) of MFSK signals has been developed. The FFTC algorithm is practical since it only requires some reasonable knowledge of a received signal. It is found that the FFTC algorithm works well in classifying 2-FSK, 4-FSK, 8-FSK, 16-FSK, and 32-FSK signals when SNR>0dB. The FFTC algorithm also gives good estimation of the frequency deviation of the received MFSK signal.
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