Abstract:

A radar target image super-resolution reconstruction method based on the joint focus/super-resolution Bayesian model is presented. Based on the joint focus/superresolution and point spread function model and using Metropolis-Hastings algorithm, the method produces a series of samples describing the probability distribution characteristic of the target scattering cross sections and defocusing parameters, thus estimates the optimum defocusing parameter and cross section elements and finally realizes the super-resolution of low-resolution  images. The method is illustrated on synthetic and measured images, and the super-resolution representations of lowresolution images are given. The experimental results indicate that the method has a good performance  in the radar image reconstruction and may be applied to exploit target information from the radar images produced by synthetic aperture radar (SAR), inverse synthetic aperture radar (ISAR) or real beam imaging radar.