DLR's Experimental SAR Research Articles

Polarimetric Dual-Baseline InSAR Building Height Estimation at L-Band

This letter generalizes a multibaseline interferometric synthetic aperture radar (InSAR) signal model to the polarimetric scenario. Based on this formulation, two high-performance spectral analysis techniques are adapted to process multibaseline Pol-InSAR observations. These new methods enhance the height estimation of scatterers by calculating optimal polarization combinations and allow the determination of their physical characteristics. Applying the proposed algorithms to urban environments, the building layover problem is analyzed by means of polarimetric dual-baseline InSAR measurements: the ground and building height are estimated. The techniques are validated using dual-baseline Pol-InSAR data acquired by DLR's Experimental SAR (E-SAR) system over Dresden city.

Fuzzy rule based classification of polarimetric SAR data

We present a classification approach for full polarimetric SAR data based on Cloude's Decomposition Theorem. The approach is rule based, making use of knowledge of both the scattering properties contained in the entropy and α-angle values plus the backscatter intensities, which lie behind the first eigenvalue of the polarimetric coherency matrix. In order to overcome imprecise decision boundaries we make use of fuzzy logic. In a final step, the derived rulebase can be supervisedly optimized by a neuro-fuzzy approach. We show the performance of our approach on a data set taken by DLR's Experimental SAR (E-SAR) in L-band.