摘要
对含微动运动的目标进行稀疏孔径逆合成孔径(ISAR)成像时,基于Chirplet分解和压缩感知(CS)的成像算法存在运算效率低、重构精度与鲁棒性差等问题。针对上述算法中存在的不足,提出了基于调幅-线性调频(AM-LFM)分解和贝叶斯正交匹配追踪(BOMP)的改进微动目标成像算法。应用该改进压缩感知(CS)算法进行微动目标成像,实验结果表明:由于改进算法采用AM-LFM分解和BOMP重构,提高了重构精度、鲁棒性与运算效率,成像效果比原算法更好。
In sparse-aperture inverse synthetic aperture radar （ISAR）imaging for micro-motiontarget,the imaging algorithm based on Chirplet components and Compressive Sensing （CS）has theproblem in computation efficiency,reconstruction accuracy and robustness. Due to the defects,proposed an improved imaging algorithm based on amplitude modulation-linear frequency modulation（AM-LFM） components and Bayesian orthogonal matching pursuit （BOMP） . Finally the improved algorithm is used for ISAR imaging,simulation shows that the improved algorithm can improve computation efficiency,reconstruction accuracy and robustness,and it’ s imaging effect is better thanoriginal algorithm.
作者
卢丁丁
张智军
杨博楠
马赢
肖冰松
LU Dingding;ZHANG Zhijun;YANG Bonan;MA Ying;XIAO Bingsong(School of Aeronautics and Astronautics Engineering,Air Force Engineering University,Xi’an 710038,China;Unit 95662 of PLA,Lasa 850000,China)
出处
《火力与指挥控制》
CSCD
北大核心
2018年第5期11-16,共6页
Fire Control & Command Control
基金
航空电子系统综合技术重点实验室和航空基金联合资助项目(20155596024)
关键词
微动运动
压缩感知
调幅-线性调频
贝叶斯正交匹配追踪
micro-motion movement
compressive sensing （CS）
amplitude modulation-linear frequency modulation （AM-LFM）
bayesian orthogonal matching pursuit（BOMP）
