基于深度分割的端到端雷达信号分选  

End-to-end radar signal sorting based on deep segmentation

作　　者：陈涛[1,2] 刘福悦 李金鑫 雷宇 CHEN Tao;LIU Fuyue;LI Jinxin;LEI Yu(College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China;Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology,Harbin 150001,China)

机构地区：[1]哈尔滨工程大学信息与通信工程学院,黑龙江哈尔滨150001 [2]先进船舶通信与信息技术工业和信息化部重点实验室,黑龙江哈尔滨150001

出　　处：《系统工程与电子技术》2023年第5期1351-1358,共8页Systems Engineering and Electronics

基　　金：国防科技基础加强计划(2019-JCJQ-ZD-067-00)资助课题。

摘　　要：针对传统的雷达信号分选方法严重依赖预置参数、先验信息和结构不灵活的问题,提出一种基于深度分割的端到端雷达信号分选方法。首先将采集到的脉冲描述字映射成脉冲序列图像,同时保留像素点对脉冲的索引;然后利用训练好的深度分割模型U-Net对脉冲序列图像分割获得像素点分类结果;最后根据像素点索引和像素点分类结果对所有脉冲进行搜索归类,整个过程采用端到端形式。实验表明,该方法能够加强对捷变参数的分选能力,如频率捷变雷达、脉组捷变频等雷达参数,以及对时频域混叠、脉冲丢失严重等未知电磁环境中信号的分选能力。Aiming at the problem that the traditional radar signal sorting method relies heavily on preset parameters and prior information and the problem of inflexible structure,an end-to-end radar signal sorting method based on deep segmentation is proposed.Firstly,collected pulse description words(PDWs)are mapped into pulse sequence images,while retaining the index of the pixel to the pulse.Secondly,the trained depth segmentation U-Net model segments the pulse sequence image to obtain the pixel classification results.Finally,all pulses are searched and sorted according to the pixel index and the pixel classification results.The whole process is carried out in an end-to-end manner.Experiments show that this method can strengthen the classification ability to sort parameters of radars such as frequency agile radar,pulse group agile radar,and other unknown electromagnetic environments with severe time-frequency domain aliasing and severe pulse loss.

关 键 词：雷达信号分选 端到端 脉冲描述字 U-Net模型 

分 类 号：TN957.51[电子电信—信号与信息处理] TP183[电子电信—信息与通信工程]