New concept & Signal Processing: to develop new efficient and robust processing algorithms in radar applications. Research mainly focused on statistical signal processing and machine learning theories for robust estimation, detection, classification and clustering, consists in developing novel methodologies based on model-driven and data-driven both approaches for enhancing performances of Radar and Hyperspectral Image processing with applications to STAP, MIMO radar, SAR and change detection.
CURRENT PHD STUDENTS
Thesis : Contributions aux traitements adaptatifs robustes pour les systèmes multi-capteurs
Jose Augustin BARRACHINA
Thesis : Complex Valued Deep Neural Networks for Radar Applications
Thesis : Robust Clustering for Satellite Image Time Series
Thesis : Spectral clustering Based Methods for Unsupervised Classification in Radar Imaging Applications
FORMER PHD STUDENTS