采用纹理特征的跳频信号盲检测算法

针对通信对抗中的跳频信号检测问题，提出了一种基于纹理特征的跳频信号盲检测算法。该算法在时频分析的基础上采用灰度共生矩阵提取信号的纹理特征，通过对纹理特征量的分割实现信号与背景噪声的分割，并运用形态学滤波去除二值化后产生的椒盐噪声；然后通过连通区域标记获得时频图中各信号的位置信息，并采用聚类分析去除定频、突发等干扰，实现跳频信号的自动盲检测。仿真结果表明，该算法可以更加有效地分割信号与背景噪声，能够在较低的信干噪比下检测出跳频信号。 

Blind detection algorithm for frequency hopping signals using texture feature

In order to detect the frequency hopping signals at the communication countermeasures, a texture feature based algorithm is proposed. In this algorithm the received signals are represented as time-frequency diagram, and texture features are extracted from the time-frequency diagram by using gray level co-occurrence matrix (GLCM). Then the background noise can be removed through the separation of texture features, and the salt-and-pepper noise after binaryzation is eliminated by morphological filtering. Then labeling all the connected components in the time-frequency diagram to get the location information, and removing the frequency-fixed and burst interference by means of clustering, so the frequency hopping signals can be detected automatically. Simulation results show that the algorithm can separate the background noise from the signals more effectively, and can detect frequency hopping signals even when the Signal Interference Noise Ratio (SINR) is low.