短波通信中的数字调制信号识别

Recognition of digital modulation signals in shortwave communications

针对目前没有有效的方法对短波通信中的调制信号进行识别的问题,提出一种基于小波包变换、高阶累积量和支持向量机的数字调制信号识别新方法.该方法提取信号经小波包变换后各频段的能量值和累积量作为特征向量,利用以支持向量机为基础的多级分类器对其进行调制识别.此分级调制识别方法与其他非分级调制识别方法相比具有较高的识别率.实验表明,针对FSK、PSK等10种调制信号在低信噪比下具有较高的识别能力,该算法在短波通信中的调制信号识别领域有较好的应用.

There has been no effective way to recognize modulation signals in shortwave communications until now. The authors developed a method for digital modulation recognition based on wavelet packet transform, high order cumulants and support vector machine. In the method, the energy values and cumulants obtained from wavelet packet transform are extracted as the eigenvectors, then hierarchical classifiers based on support vector machines are used as the classifiers to modulate and recognize the signals. This hierarchical method has a higher recognition rate than other non-hierarchical ones. Classification results for 10 modulation types including FSK, PSK etc. showed that the method has higher recognition performance in low SNR environments and it has wide application in recognition of modulated signals in shortwave communications.