Building height estimation using multibaseline L-band SAR data and polarimetric weighted subspace fitting methods

Multibaseline (MB) PolinSAR techniques are applied to the analysis of urban areas to estimate the heights of scatterers, discriminate the layover contributions and extract scattering mechanisms. This paper applies the weighted subspace fitting (WSF) method to resolve the MB-PolinSAR problem in urban areas. Considering two scatterer signal models, i.e, the coherent and distributed scatterers, WSF is optimally model adaptive compared to other High-Resolution methods. A fully polarimetric extension WSF estimator is proposed to enhance the height estimation performance and determine the physical characteristics of buildings. For computation efficiency, an analytic optimization solution is developed to maintain the search dimension of the fully WSF estimation to the one of single polarization case. The effectiveness of the proposed polarimetric WSF estimator is demonstrated using multibaseline PolInSAR data acquired by DLR’s ESAR system at L-band over an urban area of Dresden.