基于SL0压缩感知的SAR图像重构方法

SAR image reconstruction method based onSL0 compressed sensing

结合合成孔径雷达(SAR)图像特点,提出一种基于改进光滑L0范数(MSL0)的压缩感知SAR图像重构方法。该方法采用“陡峭性”更大的近似双曲函数逼近离散的L0范数,将压缩感知SAR图像重构中L0范数最小化问题转化为光滑函数的最小值优化问题。其次,针对光滑L0范数(SL0)算法因使用最速下降法产生“锯齿现象”导致增加了SAR图像重构时间、重构后的SAR图像分辨率不高等缺点,引入混合优化算法,该算法结合最速下降法与拟牛顿法的优点,提高了SAR图像重构的速度与精度。实验表明,在相同外部条件下,所提出的SAR图像重构方法各方面性能均有较大提高。

Combined with the characteristics of synthetic aperture radar(SAR),a compressed-sensing SAR image reconstruction method based on modified smoothed L0(MSL0)is proposed.The method approximates the discrete L0 norm with a larger approximation hyperbolic function of“steepness”,and transforms the L0 norm minimization problem in the compressed sensing SAR image reconstruction into the minimum optimization problem of the smooth function.Secondly,for the smoothed L0(SL0)norm algorithm,“Saw-tooth phenomenon”occur caused by using steepest descent method leads to the disadvantage of increasing the SAR image reconstruction time and the low resolution of the reconstructed SAR image,and introducing a hybrid optimization algorithm.The algorithm combines the advantages of the steepest descent method and the quasi-Newton method to improve the speed and precision of SAR image reconstruction.Experiments show that under the same external conditions,the performance of SAR image reconstruction methods proposed in this paper is greatly improved.