Adaptive Coherent Multilook GLRT for SAR Tomography Detection

In recent years, generalized likelihood ratio test (GLRT) scatterers’ detection in the context of synthetic aperture radar tomography (TomoSAR) 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 multilook 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 article, 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 M-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 (TSX) over the city of Naples (Italy) demonstrate the performance improvement of our proposed approach.

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Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/tgrs.2025.3592847
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
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article

Adaptive Coherent Multilook GLRT for SAR Tomography Detection

Karima Hadj-Rabah, Azzedine Bouaraba, Gilda Schirinzi, Nabil Haddad
IEEE Transactions on Geoscience and Remote Sensing
Synthetic Aperture Radar (SAR) Applications and Techniques
article

Adaptive Coherent Multilook GLRT for SAR Tomography Detection

Karima Hadj-Rabah, Azzedine Bouaraba, Gilda Schirinzi, Nabil Haddad
article en

Abstract

In recent years, generalized likelihood ratio test (GLRT) scatterers’ detection in the context of synthetic aperture radar tomography (TomoSAR) 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 multilook 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 article, 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 M-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 (TSX) over the city of Naples (Italy) demonstrate the performance improvement of our proposed approach.

IEEE Transactions on Geoscience and Remote SensingVol. 63
University of Salzburg (AT), Parthenope University of Naples (IT), Polytechnic School of Algiers (DZ)
Openalex Percentile: Top 75%
Synthetic Aperture Radar (SAR) Applications and Techniques
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Adaptive Coherent Multilook GLRT for SAR Tomography Detection — Karima Hadj-Rabah, Azzedine Bouaraba, et al. · IEEE Transactions on Geoscience and Remote Sensing (2025) | TGRS Research Map | TGRS