Dana El Hajjar

I joined the LISTIC laboratory (University Savoie Mont Blanc) and the L2S laboratory ( CentraleSupélec, University Paris-Saclay) in December 2022 as a PhD student under the supervision of Yajing YAN, Mohammed Nabil El Korso and Guillaume Ginolhac.

I am interested in the potential of regular Sentinel-1 A/B SAR images, as they offer both opportunities and challenges for scientists monitoring Earth deformation through SAR image time series. The primary goal of my PhD thesis is to develop a novel, robust, and sequential Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) approach that takes into account the structure of the covariance matrix and temporal decorrelation models, thereby enhancing the efficiency of the Phase Linking method. This proposed methodology will deepen our understanding of Earth deformation through SAR image time series and provide valuable insights for operational monitoring.

Selected publications

All publications are available via the Publications tab.

2024

IGARSS

Sequential Phase Linking : Progressive Integration of SAR Images for Operational Phase Estimation

El Hajjar Dana, Yan Yajing, Ginolhac Guillaume and 1 more author

International Geoscience and Remote Sensing Symposium (IGARSS 2024) 2024

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This paper introduces a novel approach for sequential estimation of the interferometric phase in the context of long Synthetic Aperture Radar (SAR) image time series. When newly acquired data arrive, the data set expands and can be partitioned into two distinct blocks. One represents the previous SAR images and the other represents the newly acquired data. The proposed approach (S-MLE-PL) exploits sequential maximum likelihood estimation of the covariance matrix of the whole data set, taking the existing data set as prior information. This approach facilitates the continuous interferometric phase estimation by incorporating the new data into the previous context. In addition, it presents the advantage of reduced computation time compared to the traditional approaches, making it a more efficient solution for operational displacement estimation.

                        
                              @article 
                              {10360230   
                                    title  = 
                                    {Sequential Phase Linking : Progressive Integration of SAR Images for Operational Phase Estimation},
                                    author = {El Hajjar Dana; Yan Yajing; Ginolhac Guillaume; El Korso Mohammed Nabil} , 
                                    journal  = {{International Geoscience and Remote Sensing Symposium (IGARSS)}} ,
                                    year = {2024},
                                    doi = {10.1109/IGARSS53475.2024.10641742},
                                    keywords = {Multi-temporal InSAR, sequential estimation, covariance matrix, phase linking} ,
                                    url = {},
                                    volume = {}, 
                                    number  =  {} , 
                                    pages  =  {11470-11473}, 
                                    month = {July},
                                    issn = {2153-6996} }