Adaptive Coherent Multi-look GLRT for SAR Tomography Detection

In recent years, Generalized Likelihood Ratio Test (GLRT) scatterers detection in the context of Synthetic Aperture Radar tomography has gained great interest from the remote sensing scientific community. This is due to its effectiveness in identifying scatterers within each single azimuth-range resolution cell, particularly in urban areas. The multi-look GLRT (M-GLRT) variant offers more satisfactory results at the expense of spatial resolution deterioration, by jointly exploiting the neighboring information of the pixel to be reconstructed. In this context, coherent and incoherent formulations can be adopted. The former provides better performance in the assumption of constant reflectivity of the pixels in the considered neighborhood, while the latter is much more robust with respect to the violation of this assumption. In this paper, an adaptive formulation of the coherent and incoherent GLRT is presented with the aim of improving scatterers’ detection and their height estimation. The method is based on an adaptive window setting, to select adjacent pixels with similar height and reflectivity characteristics. A detailed study and analysis of the proposed Adaptive Coherent Multi-look GLRT (ACM-GLRT) detector has been conducted and validated through simulations along with comparison to both standard and adaptive formulations of incoherent M-GLRT. Experimental findings from a real dataset acquired by the German TerraSAR-X over the city of Naples (Italy) demonstrate the performance improvement of our proposed approach.