Compressive Subsurface Radar Imaging: fast and smart detection of buried explosive threats

Around 100 million explosive threats are currently buried all over the world (causing at least 5,554 casualties in 2019) and a system to accurately and fast detect them still does not exist. This interdisciplinary project aims to develop an innovative subsurface radar technology, able to provide a clear, efficient, and fast detection of buried explosive threats such as landmines and Improvised Explosive Devices (IEDs). To achieve this, for the first time, this research will develop a Compressive Sensing (CS) technology able to work in dielectric media exploiting compression at both the signal processing and physical layers. Relying on CS, far fewer radar measurements will be needed to create the subsurface radar images. The project aims to play a major role in combatting the worldwide problem of humanitarian demining, having a broad impact in the society. Therefore, its scope is in alignment with the 16th Sustainable Development Goal established in the United Nations' 2030 Agenda, which seeks to promote peaceful societies, and with Horizon Europe Cluster 3 (Civil Security for Society). The fellow's research experience in subsurface imaging for the detection of buried threats together with the outstanding expertise of the supervisor in the challenging area of CS radar imaging turn this application into a great opportunity to carry out a groundbreaking research project, deliver high-impact results and foster a fruitful and long-lasting collaboration. This synergy will ensure world-leading research in radar systems due to the combined efforts of experts from different countries and backgrounds, excellent facilities at Queen's University Belfast and support from expertise on-site. This action is timely for the fellow to pursue research independence and scientific excellence with a keen eye on technology transfer, to become an internationally recognized leader in radar imaging and to enhance her research and transferable skills thanks to the planned training activities.