arXiv subjects

M. N. El Korso

Publications and source records attributed to M. N. El Korso.

3 recordsLinked to original sources

arXiv2026

Robust Expectation-Maximization for Covariance Estimation in SIRV Models with Missing Data: Application to InSAR Time Series

This paper presents a robust Expectation-Maximization framework for covariance estimation in Scale-Invariant Random Vector (SIRV) models with missing data under ignorable missingness mechanisms. By adopting an inverse-gamma prior on the scale variables, the resulting observation model leads to a complex multivariate Student-t distribution and allows closed-form E-step and M-step updates. The proposed algorithm incorporates numerical robustness techniques such as computation reuse for common observation patterns, regularized matrix inversions, and explicit enforcement of Hermitian positive semidefinite structure. Experiments on synthetic data and Sentinel-1 interferograms show effective missing value reconstruction and denoising performance under both MCAR and MNAR scenarios.

stat.ME↗

arXiv2026

Radar Detection through Rectified Flow Matching

Radar target detection in the presence of a mixture of non-Gaussian clutter and white thermal noise is a challenging problem. This paper proposes a Rectified Flow Matching-based method for radar detection, termed D-RFM. Unlike existing detectors, D-RFM learns a mapping from a standard Gaussian distribution to radar observations by capturing the underlying velocity field. Detection is then performed by inverse mapping test samples into the latent Gaussian space using the learned velocity field, with targets identified as deviations from the learned distribution. Experimental results demonstrate the efficacy of the proposed method under both Gaussian and non-Gaussian clutter plus additive white Gaussian noise, highlighting its accuracy, robustness, and computational efficiency.

eess.SP↗

arXiv2018

French SKA White Book - The French Community towards the Square Kilometre Array

The "Square Kilometre Array" (SKA) is a large international radio telescope project characterised, as suggested by its name, by a total collecting area of approximately one square kilometre, and consisting of several interferometric arrays to observe at metric and centimetric wavelengths. The deployment of the SKA will take place in two sites, in South Africa and Australia, and in two successive phases. From its Phase 1, the SKA will be one of the most formidable scientific machines ever deployed by mankind, and by far the most impressive in terms of data throughput and required computing power. With the participation of almost 200 authors from forty research institutes and six private companies, the publication of this French SKA white paper illustrates the strong involvement in the SKA project of the French astronomical community and of a rapidly growing number of major scientific and technological players in the fields of Big Data, high performance computing, energy production and storage, as well as system integration.

astro-ph.IM↗