针对常规参数进行复杂体制雷达辐射源信号分选时存在的问题,对信号双谱图分别进行频率分区和奇异值分解,二次提取其双谱分布熵和奇异谱熵作为雷达辐射源特征参数。该方法利用双谱分析可以完全抑制高斯有色噪声对信号的影响,同时保留信号的幅度和相位信息的特点,并有机地融合了双谱理论、奇异值分解和信息熵理论的各自优点,反映出信号的本质信息。采用模糊C均值聚类算法对不同信噪比条件下6种典型调制类型的雷达辐射源信号进行聚类分选实验。实验结果表明,该方法取得了较好的分选效果,克服了传统图像特征提取算法特征维数过高和聚集性差的缺点,验证了该方法的有效性。

To deal with the problems of emitter sorting caused by parameter complexity and agility of multi-function radars. The bispectrum images of radar signals are divided equally into some identical regions and singular value decomposition is used,bispectra distribution entropy and singular spectrum entropy are extracted for the cascade features. This method takes advantage of the superiority of bispectrum analysis in restraining the affection of coloured Gauss noise and retaining the amplitude and phase informations. It organically integrates the advantages of the theory of the bispectrum analysis,singular value decomposition theory and information entropy theory,and fully reflects the intrinsic signal informations. The radar signals are classified by fuzzy C-means for experimentation to demonstrate the validity of this algorithm. Experiments conducted on six typical emitter signals show that the algorithm is of preferably sorting precision under moderate SNR, and surmounts the disadvantages of higher feature dimension and deficient compactness of clusters about traditional methods for feature extraction of pictures.

国家自然科学基金资助项目;国防科技重点实验室资助项目