Recognition of dynamically varying PRI modulation via deep learning and recurrence plot

Recognition of pulse repetition interval(PRI)modulation is a fundamental task in the interpretation of radar intentions.However,the existing PRI modulation recognition methods mainly focus on single-label classification of PRI sequences.The prerequisite for the effectiveness of these methods is that the PRI sequences are perfectly divided according to different modulation types before identification,while the actual situation is that radar pulses reach the receiver continuously,and there is no completely reliable method to achieve this division in the case of non-cooperative reception.Based on the above actual needs,this paper implements an algorithm based on the recurrence plot technique and the multi-target detection model,which does not need to divide the PRI sequence in advance.Compared with the sliding window method,it can more effectively realize the recognition of the dynamically varying PRI mo dulation.

基于YOLOv5与PRI变换的无人机编队检测

针对无人机编队数量的检测,文中从信号处理角度,提出了一种基于YOLOv5与脉冲重复间隔(PRI)变换的无人机编队检测算法。首先对无人机旋翼的雷达回波微多普勒信号进行建模与参数化表征,用时频变换方法得到微多普勒时频图,然后对其中的闪烁脉冲用YOLOv5进行检测并得到每个闪烁脉冲的位置信息,最后用PRI变换对闪烁脉冲进行分选,并基于分选结果得到无人机数量的估计。实验结果表明,该方法在信噪比为2 dB时,对4架无人机编队的检测准确率能够达到90%以上。

基于雷达脉冲重复间隔设计的Radon-Fourier变换盲速旁瓣抑制

盲速旁瓣可能增加长时间相干积累方法 Radon-Fourier变换(RFT)的虚警概率并影响检测性能。为此,该文提出一种基于脉冲重复间隔(PRI)设计的盲速旁瓣抑制方法。利用不同PRI盲速旁瓣位置及速度分辨率的关系,给出了PRI具体设计方法。然后,联合处理两个相邻相参处理间隔(CPI)的RFT输出结果,在不降低RFT积累性能的情况下实现盲速旁瓣(BSSL)的抑制。最后,数值实验结果验证了该文所提方法的有效性。

基于脉冲序列间隔变换的重复周期分选方法

简要介绍了基于脉冲序列间隔变换算法,对脉冲序列间隔变换算法进行计算机仿真和分析。实际应用的结果表明,基于脉冲序列间隔变换的重复周期分选方法对固定和参差重复周期形式的雷达脉冲序列的分选有较好的效果。