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Research projects


Modern aircraft structures have to comply with severe requirements: they have to be light as well as safe. These requirements lead to an increased use of composite materials in the aircraft industry. However, new materials also require new techniques in order to inspect aircraft components during production in a non-destructive way.

The primary goal of the DOTNAC project is to develop a safe, contact-free, high resolution, and potentially on-site NDT tool based on terahertz (THz) waves, which will be easy to integrate in industrial facilities, and allowing the detection of surface, subsurface and in-depth defects in a variety of composite materials used in aeronautics. The developed NDT tool will fill in the performance gaps that are still present amongst the established NDT techniques and will therefore be an extremely useful tool in NDT in terms of sensor fusion.


This study mainly focusses on how to retrieve the position of the sensor nodes of a wireless sensor network and with which precision this can be done (assuming the nodes don’t have a GPS module on board). How the topology of the wireless network could be controlled in order to optimise the network for given scenarios is also investigated. The goal of this study is not only to have a theoretical approach of the problem, but also to implement the most promising methods or algorithms on a real sensor network.


  1. Mathias Becquaert. Compressed Sensing for Microwave In-Depth Imaging. PhD thesis, Royal Military Academy and Vrije Universiteit Brussel, May 2019.
  2. Mathias Becquaert, Edison Cristofani, Marijke Vandewal, Johan Stiens, and Nikolaos Deligiannis. Online sequential compressed sensing with weighted multiple side information for through the wall imaging. In URSI Benelux Forum 2018, pages 1-5. URSI, 1 2018.
  3. Edison Cristofani, Mathias Becquaert, Sébastien Lambot, Marijke Vandewal, Johan Stiens, and Nikos Deligiannis. Random subsampling and data preconditioning for ground penetrating radars. IEEE Access, pages 1-16, 2018.
  4. Edison Cristofani, Osama Mahfoudia, Mathias Becquaert, Xavier Neyt, François Horlin, Nikolaos Deligiannis, Johan Stiens, and Marijke Vandewal. Exploring side information for DVB-t-based passive radars. In URSI Benelux Forum 2018, pages 1-1. URSI, 1 2018.
  5. Mathias Becquaert, Edison Cristofani, Johan Stiens, Marijke Vandewal, and Nikos Deligiannis. Compressed Sensing SAR Through-the-Wall Imaging with Side Information. In 26th URSI Benelux Forum, Brussels, Belgium, 2017. URSI.
  6. Edison Cristofani, Osama Mahfoudia, Mathias Becquaert, Xavier Neyt, François Horlin, Nikos Deligiannis, Johan Stiens, and Marijke Vandewal. Compressive Sensing and DVB-T-Based Passive Coherent Location. In 26th URSI Benelux Forum, Brussels, Belgium, 2017. URSI.
  7. Mathias Becquaert, Edison Cristofani, Gokarna Pandey, Marijke Vandewal, Johan Stiens, and Nikos Deligiannis. Compressed sensing mm-wave SAR for non-destructive testing applications using side information. In 2016 IEEE Radar Conference (RadarConf), number 2, pages 1-5. IEEE, May 2016.
  8. Edison Cristofani, Mathias Becquaert, Gokarna Pandey, Marijke Vandewal, Nikos Deligiannis, and Johan Stiens. Compressed Sensing And Defect-Based Dictionaries For Characteristics Extraction In Mm-Wave Non-Destructive Testing. In Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), 2016 41st International Conference on, Copenhagen, Denmark, 2016.
  9. M Vandewal, M Becquaert, and F Moustier. Optronique et Radar. Ecole Royale Militaire, 2014.
  10. M Becquaert, E Cristofani, and M Vandewal. On the applicability of compressive sensing on FMCW synthetic aperture radar data for sparse scene recovery. In European Microwave Week 2013, EuMW 2013 - Conference Proceedings; EuRAD 2013: 10th European Radar Conference, pages 9-12, October 2013.
  11. Anna Brook, Edison Cristofani, Mathias Becquaert, Ben Lauwens, Joachim Jonuscheit, and Marijke Vandewal. Applicability of compressive sensing on three-dimensional terahertz imagery for in-depth object defect detection and recognition using a dedicated semisupervised image processing methodology. Journal of Electronic Imaging, 22(2):21004, 2013.
  12. Edison Cristofani, Mathias Becquaert, and Marijke Vandewal. Performance of 2D Compressive Sensing on Wide-Beam Through-the-Wall Imaging. Journal of Electrical and Computer Engineering, 2013(636972):1-11, 2013.
  13. E Cristofani, M Becquaert, and M Vandewal. Ultra-Wideband , Non-Destructive Testing SAR Systems towards Compressive Sensing. In 1st International workshop on Compressed Sensing applied to Radar (CoSeRa 2012), number May, pages 14-16, Bonn, Germany, May 2012.