摘要
针对合成孔径时间短、逆合成孔径雷达数据成像质量差的问题,本研究提出一种基于迭代自适应恢复缺失数据(missing-data iterative adaptive processing approach,MIAA)的短孔径数据的逆合成孔径雷达(inverse synthetic aperture radar,ISAR)超分辨率成像方法。该方法利用MIAA对ISAR回波数据的方位向进行扩展,从而增加数据的方位向长度,提高成像质量。仿真和实测均表明该方法能够有效扩展回波数据的方位向长度,提高短孔径条件下的成像质量。
For the problem of poor imaging quality of short synthetic aperture time ISAR data,an imaging method with super resolution for ISAR with short aperture data based on missing-data iterative adaptive processing approach(MIAA)is proposed in this paper,which expands the azimuthal data to improve the imaging quality.This method uses MIAA to expand the data in the azimuth direction of the ISAR echo data,so as to increase the azimuth length of the data and enhance the imaging quality.The simulations and measured data both verify that the method can effectively extend the echo data in azimuth and improve the imaging quality under segmental aperture.
作者
张蓓
周波
白昊
石川
王雷钢
ZHANG Bei;ZHOU Bo;BAI Hao;SHI Chuan;WANG Leigang(Unit 63892 of PLA,Luoyang 471003,China;Unit 32201 of PLA,Baicheng 137000,China)
出处
《系统仿真技术》
2024年第1期91-95,共5页
System Simulation Technology
关键词
雷达
逆合成孔径雷达
短孔径
超分辨率成像
迭代自适应方法
radar
inverse synthetic aperture radar
short aperture
super resolution
iterative adaptive approach
