Gridless GLRT for Tomographic SAR Detection Using Particle Swarm Optimization Algorithm

• Published in: IEEE geoscience and remote sensing letters Vol. 21; pp. 1 - 5
• Main Authors: Haddad, Nabil, Budillon, Alessandra, Hadj-Rabah, Karima, Bouaraba, Azzedine, Harkati, Lekhmissi, Benbouzid, Mohammed Amine, Schirinzi, Gilda
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Algorithms; Computational efficiency; Detectors; Generalized likelihood ratio test (GLRT) detection; Geoscience and remote sensing; gridless GLRT; Height; height estimation; Image reconstruction; Likelihood ratio; Linear programming; Minimization; Particle swarm optimization; particle swarm optimization (PSO); Radar detection; Resolution cell; Root-mean-square errors; SAR (radar); Synthetic aperture radar; synthetic aperture radar (SAR) tomography (TomoSAR); Three dimensional models; Tomography; Vectors
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2024.3485883

The detection of multiple scatterers within each resolution cell is an open research subject in synthetic aperture radar (SAR) tomography (TomoSAR). For over a decade, the generalized likelihood ratio test (GLRT) detector has been implemented along with its variants, allowing the generation of height maps and 3-D point clouds with good precision. However, they are limited by the grid search during the optimization of the maximum likelihood function. In order to mitigate this, we propose a gridless version of GLRT where the particle swarm optimization (PSO) method is used to locate the minima. The conducted analysis of the proposed detector with respect to the state-of-the-art methods behavior on simulated and real datasets proved the effectiveness of PSO-GLRT in terms of height accuracy and computational cost. The evaluation metrics, root-mean-square error (RMSE), accuracy, and completeness, have been used as a quantitative improvement indicator for estimated height assessment.