摘要
逆合成孔径雷达(Invese Synthetic Aperture Radar, ISAR)因其对空间、地面和海上运动目标的高分辨率成像能力而在遥感中得到广泛应用,但是实际中使用ISAR对机动目标成像时,存在回波信息不完整、成像分辨率低、易散焦等问题。针对以上问题,提出一种快速稀疏贝叶斯学习重构信号的成像方法,首先建立符合回波特性含参数γ的稀疏基矩阵,然后使用快速边缘似然函数最大化算法对稀疏孔径信号进行求解成像,仿真验证成像效果良好。
Inverse synthetic aperture radar(ISAR)is widely used in remote sensing because of its high-resolution imaging ability for moving targets in space,ground and sea.However,when ISAR is used to image maneuvering tar-gets in practice,there are some problems such as incomplete echo information,low imaging resolution and easy defo-cusing.In view of the above problems,this paper proposes a fast sparse Bayesian learning reconstruction signal ima-ging method.Firstly,a sparse basis matrix with parametersγwas established,and then the fast edge likelihood func-tion maximization algorithm was used to solve the sparse aperture signal imaging.Simulation results show that the ima-ging effect is fine.
作者
朱瀚神
胡文华
郭宝锋
朱常安
ZHU Han-shen;HU Wen-hua;GUO Bao-feng;ZHU Chang-an(Shijiazhuang Campus of Army Engineering University,Shijiazhuang Hebei 050003,China)
出处
《计算机仿真》
北大核心
2023年第5期43-48,63,共7页
Computer Simulation
基金
空间目标T/R-R型雷达稀疏孔径融合成像技术研究(F2019506031)
空间目标ISAR多雷达融合成像技术研究(KYSZJQZL2020)。
