Sidelobe Suppression of Squinted SAR Complex Data Based on Minimum Image Sharpness

Sidelobe suppression is of particular importance in the SAR image quality improvement. However, the range and azimuth sidelobes are coupled and non-orthogonal in squinted SAR images, which makes traditional methods ineffective. This letter presents a sidelobe suppression method for squinted SAR complex data based on the SAR convolution model and minimum image sharpness. First, the convolution model of SAR images is revised with the subpixel offset. Then, the sidelobe suppression is achieved by deconvolution pixel by pixel. Innovatively, a convex optimization based on minimum image sharpness is built and solved to estimate the unknown and variant subpixel offset of each target. In addition, a new factor based on integrated side lobe ratio (ISLR) is applied for efficiency improvement. Finally, results on the squinted spaceborne SAR real data verify the effectiveness of the proposed method both in sidelobe suppression and the maintenance of amplitude-phase characteristics.