  Radar interferometry usually exploits two complex-valued radar images with
the same resolution to extract terrain elevation information. This paper
considers the interferometry using two radar images with different resolutions,
which we refer to as dual-resolution radar interferometry. We find that it is
feasible to recover a high-resolution interferogram from a high-resolution
image and a low-resolution one. We formulate the dual-resolution interferometry
into a compressive sensing problem, and exploit the wavelet-domain sparsity of
the interferogram to solve it. Due to the speckle effect in coherent radar
imaging, the sensing matrix of our model is expected to have small mutual
coherence, which guarantees the performance of our method. In comparison with
the conventional radar interferometry methods, the proposed method reduces the
resolution requirement of radar image acquisition. It therefore can promote
wide coverage, low sampling/data rate and storage cost. Numerical experiments
on Sentinel-1 data are made to validate our method.
