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在通信系统中经常遇到的许多非平稳信号都具有循环平稳特性,可以用循环谱的方法来识别。但当信号本身的频谱结构比较复杂、噪声成分过大或噪声本身也具有循环平稳特性时,解调效果就不是很理想。针对循环谱识别信号的这一局限性,文中在介绍循环谱原理和识别特性的基础上,研究了几种典型通信信号的谱相关性,并提出了基于小波包与循环谱的识别技术,即先采用小波包进行软阈值消噪,再结合各自不同的循环谱特性进行识别。通过大量实验仿真表明,该方法具有很好的噪声抑制能力,能达到较好的识别效果。
Many nonstationary signals often encountered in communications systems have cyclostationary characteristics that can be identified by cyclic spectrum methods. However, the demodulation effect is not very satisfactory when the signal itself has a complicated frequency spectrum structure, an excessive noise component or a cyclostationary noise itself. Aiming at the limitation of the identification signal of cyclic spectrum, this paper introduces the spectral correlation and recognition characteristics of several typical communication signals, and proposes the identification technology based on wavelet packet and cyclic spectrum, that is, Firstly, the wavelet packet is used to denoise the soft threshold, and then the characteristics of different cyclic spectra are identified. Through a large number of experimental simulation shows that the method has good noise suppression, can achieve better recognition.