基于全脉冲的周期信号样本提取技术

现代电子战中，传统的辐射源分选识别方法无法在密集的信号环境中快速有效地对复杂体制雷达进行分选识别，造成系统漏警。基于上述情况，提出了一种基于脉冲样本序列自提取的分选算法。这种算法利用雷达信号脉冲序列的周期性和相关性，实现对模板序列的自动提取，从而可实现全脉冲序列中小样本数或脉间规律复杂的雷达信号的分选。仿真实验表明，在全脉冲数据量级适中的情况下，该算法可以有效提取目标模板序列。

The periodic signal sample extraction technology based on full pulse

In modern electronic warfare ,the traditional source separation identification method which could cause system leakage alarm ,can not be used to identify the separation in dense signal environment for complex system of radar quickly and efficiently .Based on the above situation ,a kind of sorting algorithm based on pulse sample sequence from the extraction is put forward .This algorithm uses periodicity and correlation of radar signal pulse sequence to implement automatic extraction of template sequence ,and thus it can realize full pulse sequence between medium and small sample or pulse regularity of complex radar signal sorting . Simulation results show that under the condition of the moderate scale full pulse data , the algorithm can effectively extract the target template sequence .