Detection of structural targets using ground-based interferometric synthetic aperture radar and augmented reality

Saeed Sotoudeh; Stephen Uzor; Livia Lantini; Kevin Munisami; Fabio Tosti

doi:10.1117/12.2675946

9 August 2023 Detection of structural targets using ground-based interferometric synthetic aperture radar and augmented reality

Saeed Sotoudeh, Stephen Uzor, Livia Lantini, Kevin Munisami, Fabio Tosti

Author Affiliations +

Proceedings Volume 12621, Multimodal Sensing and Artificial Intelligence: Technologies and Applications III; 1262102 (2023) https://doi.org/10.1117/12.2675946
Event: SPIE Optical Metrology, 2023, Munich, Germany

Abstract

Structural Health Monitoring (SHM) is critical to ensuring the safety of structures such as bridges, tunnels, and dams. Despite some sensors being highly accurate, it is not always feasible to interrupt the serviceability of the structure for data collection. Within this framework, remote sensing methods such as the Ground-Based Interferometric Synthetic Aperture Radar (GB-SAR) have shown their capability in remotely collecting data of multiple targets simultaneously with a high sampling rate. However, detecting targets in their exact position is currently an area that requires further investigation for this technology. The present research focuses on developing a field investigation methodology to limit uncertainties and raise awareness about the significance of data collected by GB-SAR aided by augmented reality (AR). To this effect, head-mounted and mobile AR can support the use of techniques, such as GB-SAR, which work on fundamental geometrical principles, by providing guidance markers in real time for positional and reference information. The integration of both technologies can allow to pre-visualise the optimal position for data collection by aiding to match the structural targets under investigation within the area of interest. The proposed methodology is here implemented in clinical laboratory conditions to investigate the sensor’ sensitivity against testing parameters, such as the radar position and the distance to targets. The proposed methodology will contribute to collecting data with a higher accuracy and a lower uncertainty compared to other non-destructive methods utilised in the field. This study demonstrates the potential of using AR to enhance remote sensing methods for SHM and it builds up the foundation for future development into a more comprehensive SHM approach.

Conference Presentation

Citation Download Citation

Saeed Sotoudeh, Stephen Uzor, Livia Lantini, Kevin Munisami, and Fabio Tosti "Detection of structural targets using ground-based interferometric synthetic aperture radar and augmented reality", Proc. SPIE 12621, Multimodal Sensing and Artificial Intelligence: Technologies and Applications III, 1262102 (9 August 2023); https://doi.org/10.1117/12.2675946

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