Comparison of different polarimetric tomographic estimation techniques with respect to LiDAR measurements for the 3-D characterization of buildings using intermediate resolution L-band SAR data sets

Abstract:
This paper addresses 3-D characterization of buildings using diverse tomographic techniques. Due to their high resolution, parametric tomographic estimators likeMUSIC,Maximum likelihood (ML) and subspace fitting estimators are presented and used to to resolve scatterers’ layover problem and to extract their physical features. Considering the statistical behaviors of scatterers generally encountered in SAR images, conventional estimators may have some limitations. Dealing with different scattering natures, Weighted Subspace Fitting (WSF) methods are hence applied to estimate building heights. Based on Noise Subspace Fitting (NSF), a fully polarimetric (FP) estimator, named FP-NSF, is developed as well as its analytic solution. These estimators are applied to dual-baseline PolInSAR data acquired by DLR’s ESAR at L-band overDresden city, Germany. The estimates of building heights are validated against LiDAR measurements.