基于高次频谱对称Holder系数的雷达信号分选方法

针对复杂战场电磁环境下，传统基于全脉冲参数的分选算法准确率下降这一问题，本文提出一种提取信号高次频谱对称Holder系数作为脉内特征的信号分选方法。该方法首先利用对称Holder系数法提取信号高次频谱的脉内特征，而后将提取到的脉内特征参数与稳定的脉间参数组成新的特征向量，最后使用K-means算法对信号进行分选。信号的高次频谱对称Holder系数作为一种脉内特征，相比于一次频谱相像系数具有更大的寻优空间。将该特征加入信号特征向量可使新的特征向量具有更强的可分性。仿真实验结果表明，加入该特征，并使用新的特征向量，能够有效提高对不同种调制类型雷达信号的分选正确率。，使用新的特征向量能有效提高雷达信号分选正确率。 

Radar signal sorting method based on the symmetric Holder coefficients of high-order spectrum

Aiming at the problem that the accuracy rate of the traditional sorting algorithms based on full pulse parameters is reduced in the complex electromagnetic environment of battlefields, this paper proposes a signal sorting method, which extracts the symmetrical Holder coefficients of the higher-order spectrums of the signals as the in-pulse features. This method first uses the symmetric Holder coefficient method to extract the intra-pulse features of the higher-order spectrums of the signals, and then combines the extracted intra-pulse feature parameters and the stable inter-pulse parameters into a new feature vector, and finally uses the K-means algorithm to sort the signals. As an intra-pulse feature, the symmetric Holder coefficients of high-order spectrum have a larger space for optimization than the resemblance coefficients of 1st-order spectrum. Adding this feature to the signal feature vector can make the new feature vector more separable. Simulation experiment results show that adding this feature and using the new feature vector can effectively improve the sorting accuracy of radar signals of different modulation types.