基于联合聚焦/超分辨模型和M-H算法的雷达图像重建  

Radar image reconstruction based on the joint autofocus/super-resolution model and the numerical M-H algorithm

作　　者：朱正为[1,2] 周建江[1] 

机构地区：[1]南京航空航天大学信息科学与技术学院,江苏南京210016 [2]西南科技大学信息工程学院,四川绵阳621010

出　　处：《光电子．激光》2011年第5期778-782,共5页Journal of Optoelectronics·Laser

基　　金：院士基金资助项目(2008041001);装备预研重点基金资助项目(N0601041)

摘　　要：针对雷达目标图像,基于散射/成像模型,利用Metropolis-Hastings(M-H)迭代算法,给出了一种数字M-H贝叶斯联合聚焦/超分辨重建方法,通过产生一系列描述目标散射截面(RCS)和散焦参数概率分布特征的样本,从而获得目标RCS元和散焦参数的最佳估计,最终实现低分辨率图像的超分辨率重建。以合成与实测图像数据为例,对本文方法进行了演示,同时基于信噪比(SNR)指标,对其重建性能进行了比较和评估。实验结果表明,本文提出的方法对雷达图像重建效果良好,可用于合成孔径雷达、逆合成孔径雷达及实波束成像等雷达图像的重建。A radar target image reconstruction approach combining the joint autofocus/super-resolution model and the numerical Metropolis-Hastings（M-H） Bayesian technique is presented.The approach is based on the scattering/imaging model and adopts the numerical M-H algorithm to produce a series of samples that characterize the probability distributions of the target scattering cross sections and defocusing parameters,so the optimal estimation of the defocusing parameters and the scattering cross section elements is realized,and finally the super-resolution reconstruction of a low-resolution image is realized.The proposed approach was illustrated on synthetic and measured data and its reconstruction performance was compared and assessed by using the metric signal-to-noise ratio.The experimental results indicate that the proposed approach has good performance in the radar image reconstruction,and may be applied for the radar images produced by synthetic aperture radar,inverse synthetic aperture radar and beam imaging radar.

关 键 词：雷达图像 联合聚焦/超分辨 贝叶斯方法 Metropolis-Hastings(M-H)算法 

分 类 号：TN911.73[电子电信—通信与信息系统]