Three-Dimensional Structural Parameter Inversion of Buildings by Distributed Compressive Sensing-Based Polarimetric SAR Tomography Using a Small Number of Baselines

An important condition for urban studies is quantitative acquisition of spatial information, e.g., three-dimensional (3-D) structural parameters of buildings. Synthetic aperture radar tomography (TomoSAR) provides scene reflectivity estimation along azimuth, range, and elevation coordinates. For a small number of acquisitions and their irregular spacing, however, the common Fourier-based 3-D SAR-focusing approaches, even compressive sensing (CS)-based methods, bring about some imaging quality problems. This paper addresses the 3-D imaging of buildings based on the framework of CS using fully polarimetric (FP) multibaseline SAR interferometric (MB-InSAR) tomography at C-band. In this paper, we propose a new distributed CS-based FP MB-InSAR tomography method (FP-DCS TomoSAR method), which is a new polarimetric spectral analysis method based on distributed compressive sensing (DCS), model order selection, and maximum-likelihood parameter estimation for 3-D structural parameter reconstruction. Compared to the CS method, the FP-DCS TomoSAR method takes advantage of the intersignal correlations between neighboring azimuth-range pixels as well as between polarimetric channels to attain higher superresolution imaging and elevation estimation accuracy. Numerical results on simulated and real data validate the effectiveness of this novel technique by using FP C-band data acquired by Radarset-2 and are compared with the FP noise subspace fitting estimator.