  Interferometric Synthetic Aperture Radar (InSAR) Imaging methods are usually
based on algorithms of match-filtering type, without considering the scene's
characteristic, which causes limited imaging quality. Besides, post-processing
steps are inevitable, like image registration, flat-earth phase removing and
phase noise filtering. To solve these problems, we propose a new InSAR imaging
method. First, to enhance the imaging quality, we propose a new imaging
framework base on 2D sparse regularization, where the characteristic of scene
is embedded. Second, to avoid the post processing steps, we establish a new
forward observation process, where the back-projection imaging method is
embedded. Third, a forward and backward iterative solution method is proposed
based on proximal gradient descent algorithm. Experiments on simulated and
measured data reveal the effectiveness of the proposed method. Compared with
the conventional method, higher quality interferogram can be obtained directly
from raw echoes without post-processing. Besides, in the under-sampling
situation, it's also applicable.
