雷达辐射源信号双谱二次特征提取方法

现有的双谱特征提取方法可以满足信号分类识别，但是出现了交叉项、平凡双谱以及特征维数过高等一些问题。针对以上问题，提出一种双谱二次特征提取方法，将双谱转化为灰度图像，以灰度值表示双谱幅度；再利用图像处理技术提取双谱二次特征，提取出能够表征辐射源信号双谱图像纹理信息的灰度共生矩阵特征集；将该特征集与Hu-不变矩特征集进行对比实验。仿真结果表明：该方法具有更好的分类识别性能，对于CW、LFM和NLFM信号的平均识别率均达90%以上。

A Method of Feature Extracting Bispectrum Cascade from Radar Emitter Signal

New Problems such as redundancy bispectrums, cross-items and possess too high feature dimension still arise though the existing methodes of bispectrum feature extraction can meet the needs of signal classification and recognition at present. A new bispectrum cascade feature extraction method is proposed. Firstly, the bispectrum is converted to gray image, and the amplitude of bispectrum is denoted by gray value. Secondly, the bispectrum cascade feature is extracted based on image processing technique. The gray level co-occurrence matrix (GLCM) cascade feature can specify the bispectrum image texture information of radar emitter signal. Finally, the comparative experiment is made. The result shows that the GLCM features are superior to Hu-invariant moment features greatly in the aspect of performing radar signal classification and recognition.