基于CNN的高速运动目标ISAR成像方法研究  

CNN Based ISAR Imaging of High-Speed Moving Targets

作　　者：张宇 李云涛 郭永辉 李永刚 何永华 柴恬怡 ZHANG Yu;LI Yuntao;GUO Yonghui;LI Yonggang;HE Yonghua;CHAI Tianyi(University of Aerospace Engineering,Graduate School,Beijing 101000 China;University of Aerospace Engineering,Department of Electronics and Optics,Beijing 101000 China)

机构地区：[1]航天工程大学研究生院,北京101000 [2]航天工程大学电子与光学系,北京101000

出　　处：《电光与控制》2023年第2期99-105,共7页Electronics Optics & Control

摘　　要：在高速运动目标逆合成孔径雷达(ISAR)成像中,基于传统线性调频(LFM)信号参数估计进行相位补偿的方法存在计算复杂和误差大等问题,对此提出一种基于卷积神经网络(CNN)的线性调频信号调频斜率估计方法。首先采用Wigner-Ville分布的时频分析方法对一定范围调频斜率的线性调频信号生成时频图像构建训练集;其次将高速运动目标回波信号经Wigner-Ville分布处理的时频图输入到卷积神经网络中,对回波信号调频斜率进行识别;接着通过识别的调频斜率对目标速度进行反演,进而构建补偿信号并对回波信号进行相位补偿;最后通过距离多普勒成像算法处理后可得到清晰的ISAR像。仿真实验结果表明了所提方法的有效性。Considering that in Inverse Synthetic Aperture Radar(ISAR) imaging of high-speed moving targets,the phase compensation method based on traditional Linear Frequency Modulated(LFM) parameter estimation has such problems as complex calculation and large errors,a new approach based on Convolutional Neural Network(CNN) is proposed to estimate the frequency modulation slope of chirp signals.First,Wigner-Ville distribution time-frequency analysis method is used to generate time-frequency image training set for LFM signal with a certain range of frequency modulation slope.Secondly,the time-frequency image of the high-speed moving target echo signal processed by Wigner-Ville distribution is input into the CNN to identify the frequency modulation slope of the echo signal.Then,the target velocity is inversed by the identified FM slope,the compensation signal is constructed and phase compensation is made to the echo signal.Finally,clear ISAR image is obtained through the processing of Range-Doppler imaging algorithm.Simulation results show the effectiveness of the proposed method.

关 键 词：高速运动目标 ISAR成像 卷积神经网络 WIGNER-VILLE分布 

分 类 号：TN95[电子电信—信号与信息处理]