基于高斯平滑与模糊函数等高线的雷达辐射源信号分选

雷达辐射源信号分选是电子侦察系统、威胁告警系统的关键步骤.针对现有基于模糊函数的复杂体制雷达辐射源信号分选方法信息利用率低、易受噪声影响等问题, 提出一种基于模糊函数等高线的分选新方法; 首先, 对信号的模糊函数进行高斯平滑处理并绘制其等高线作为进一步的特征提取对象; 其次, 从图像处理的角度提取正外接矩和方向角作为雷达信号分选的特征向量; 最后, 用核模糊C均值聚类算法对特征向量进行分选.仿真实验表明, 所提方法在8 dB以上的固定信噪比环境下分选6类典型信号的成功率均为100 %, 即使在0 dB环境下, 分选成功率也保持在89.04 %以上; 在0 ~ 20 dB动态信噪比环境下分选成功率达到96.36 %.实测数据验证, 所提特征提高了5种外场辐射源信号的分选效果, 可作为经典5参数的有效补充. 此外, 所提特征还具备较低的计算量, 提取单个信号特征的耗时仅为0.24 s, 具有一定的工程价值.

A Sorting Method for Radar Emitter Signals Based on the Gaussian Smoothing and Contour Lines of Ambiguity Function

Sorting radar emitter signals is the key step of electronic reconnaissance system and threat warning system. Existing radar emitter signal sorting methods based on ambiguity function have many problems, such as low information utilization and susceptibility to noise. In this paper, a novel sorting method based on contour lines of ambiguity function is proposed. First, an ambiguity function is processed by using a Gaussian operator and contour lines are created as object of feature extraction. Then, a positive bounding rectangle and a direction angle are extracted as the feature vector from the perspective of image processing. Finally, the kernel fuzzy C-means clustering algorithm is used to sort the feature vector. The simulated experiments show that the success rate of sorting six kinds of typical signals by proposed method not only achieves 100 % in fixed SNR environment above 8 dB, but also keeps above 89.04 % in 0 dB. In addition, the measured data show that the proposed features can improve the sorting effect of five kinds of outfield emitter signals, which can be used as an effective complement to the classical five parameters. Besides, the proposed feature also has lower computational complexity, the feature extraction time of one signal is only 0.24 s, which indicated the engineering value of the proposed method.