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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。
According to the scattering / imaging model and the Metropolis-Hastings (MH) iterative algorithm, a digital MH Bayesian joint focusing / super-resolution reconstruction method is proposed for radar target image. By generating a series of description of target scattering cross section (RCS) And defocus parameters of the probability distribution characteristics of the sample, so as to obtain the best RCS target and defocus parameters of the best estimate, and ultimately low resolution image super resolution reconstruction. Taking the synthetic and measured image data as an example, this method is demonstrated, and its reconstruction performance is compared and evaluated based on the signal-to-noise ratio (SNR) index. The experimental results show that the proposed method is effective in radar image reconstruction and can be used to reconstruct radar images such as Synthetic Aperture Radar, Inverse Synthetic Aperture Radar and Real Beam Imaging.