Multi-pass SAR interferometry for 3D reconstruction of complex mountainous areas based on robust low rank tensor decomposition

Abstract

During the past decades, multi-pass SAR interferometry (InSAR) techniques have been developed for retrieving geophysical parameters such as elevation, over large areas. Conventional method such as periodogram usually requires a fairly large SAR image stack (usually in the order of tens), in order to achieve reliable estimates of these parameters. However, when it comes to large-area processing, it is time-consuming and luxury to obtain a sufficient number of SAR images for the reconstruction. In this paper, we demonstrate a novel multi-pass InSAR method for 3D reconstruction using low rank tensor decomposition. By exploiting the low rank prior knowledge in the multi-pass InSAR stack, simulations show that the proposed method can improve the accuracy of elevation estimates by a factor of two, compared to the stateof-the-art InSAR filtering methods, such as SqueeSAR. The capability of the proposed algorithm is also demonstrated on real data using one TanDEM-X InSAR stack of a complex mountainous area.