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

压缩式地下雷达成像：快速、智能地检测埋藏的爆炸物威胁

• 批准号: EP/X022951/1
• 负责人: Maria Garcia-Fernandez
• 金额: $ 24.26万
• 依托单位: Queen's University Belfast
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX022951%2F1
• 关键词: Compressive; Subsurface; Radar; Imaging; fast

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.

目前，全球约有1亿枚爆炸物被埋在地下（2019年至少造成5,554人伤亡），而准确、快速检测爆炸物的系统仍然不存在。这个跨学科项目旨在开发一种创新的地下雷达技术，能够提供一个清晰，高效，快速检测埋在地下的爆炸物威胁，如地雷和简易爆炸装置（IED）。为了实现这一目标，这项研究将首次开发一种压缩传感（CS）技术，该技术能够在电介质中工作，在信号处理和物理层都利用压缩。依靠CS，创建地下雷达图像所需的雷达测量将少得多。该项目旨在为解决人道主义排雷这一世界性问题发挥重要作用，在社会上产生广泛影响。因此，其范围与联合国2030年议程中旨在促进和平社会的第16个可持续发展目标以及地平线欧洲第3组（社会民事安全）相一致。该研究员在地下成像检测隐藏的威胁方面的研究经验，以及主管在CS雷达成像这一具有挑战性的领域的杰出专业知识，使这一应用成为一个很好的机会，可以开展开创性的研究项目，提供高影响力的结果，并促进富有成效的长期合作。由于来自不同国家和背景的专家的共同努力，贝尔法斯特女王大学的一流设施以及现场专业知识的支持，这种协同作用将确保世界领先的雷达系统研究。这一行动是及时的研究员追求研究的独立性和科学卓越与技术转让的敏锐眼光，成为国际公认的领导者在雷达成像和提高她的研究和转让技能由于计划的培训活动。

项目成果

Automated Metrics to Assess the Performance of Computational Imaging Systems

评估计算成像系统性能的自动化指标

• DOI: 10.1109/cama57522.2023.10352756
• 发表时间: 2023
• 作者: García-Fernández M

Range Migration Algorithm for a Multistatic 3D Compressive Computational Imaging System with Dynamic Metasurface Aperture

• DOI: 10.23919/irs57608.2023.10172481
• 发表时间: 2023-05
• 期刊: 2023 24th International Radar Symposium (IRS)
• 作者: Vasiliki Skouroliakou;A. Molaei;M. García-Fernández;G. Álvarez-Narciandi;O. Yurduseven

Comparison of Scanning Strategies in UAV-Mounted Multichannel GPR-SAR Systems Using Antenna Arrays

使用天线阵列的无人机搭载多通道 GPR-SAR 系统扫描策略比较

• DOI: 10.1109/jstars.2024.3351602
• 发表时间: 2024
• 期刊: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• 影响因子: 5.5
• 作者: García-Fernández M

Frequency-Diverse Metasurface Antenna for Computational Through-Wall Imaging

• DOI: 10.23919/eucap57121.2023.10133569
• 发表时间: 2023-03
• 期刊: 2023 17th European Conference on Antennas and Propagation (EuCAP)
• 作者: M. García-Fernández;G. Álvarez-Narciandi;O. Yurduseven

Array-Based Ground Penetrating Synthetic Aperture Radar on Board an Unmanned Aerial Vehicle for Enhanced Buried Threats Detection

• DOI: 10.1109/tgrs.2023.3272982
• 发表时间: 2023-01-01
• 期刊: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
• 影响因子: 8.2
• 作者: Garcia-Fernandez, Maria;Alvarez-Narciandi, Guillermo;Las-Heras, Fernando
• 通讯作者: Las-Heras, Fernando