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Investigating the Dynamic Behaviour of Civil Structures by Integration of Ground-Based Interferometric Radar and Augmented Reality 
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Ensuring safety of civil infrastructure is a crucial goal in structural health monitoring (SHM). Amongst the variety of monitoring sensors, the Ground-Based Interferometric Radar (GBIR) systems have recently gained attention for their advantages such as the very high resolution and fast data collection, as opposed to other conventional methods [1]. However, this technology suffers from precise target location when the acquisition is carried out in dynamic conditions. For this purpose, external reflectors need to be installed in the portion of the structure under investigation, to which then the signal response is assumed to be related.Considering this, the present research focuses on the investigation of the dynamic response of structures using GBIR aided with augmented reality (AR) [2]. AR assisted in controlling the position of the targets inside the radar’s beam of radiation and creating different acquisition scenarios in the same range based on a combination of their number and position. Dynamic excitations were applied in the field using light weight deflectometer (LWD) [3], and their effects on the collected signal were investigated using empirical mode decomposition (EMD) signal processing technique across the different scenarios. This allowed to have a better understanding of the signal response for multiple targets or at the boundaries of the signal footprint.Results show that for data capturing using GBIR systems, AR can enhance the data quality by better controlling the collection phase. In addition, the use of multi-dimensional signal processing techniques, such as the EMD, facilitated a more comprehensive understanding of the signal response in complex scenarios. Keywords: Structural health monitoring (SHM), Ground-based interferometric radar (GBIR), Augmented reality (AR), dynamic excitation, Empirical mode decomposition (EMD). AcknowledgementsThis research was funded by the Vice-Chancellor’s PhD Scholarship at the University of West London. References[1] M. Pieraccini, M. Fratini, F. Parrini, C. Atzeni, and G. Bartoli, “Interferometric radar vs. accelerometer for dynamic monitoring of large structures: An experimental comparison,” NDT and E International, vol. 41, no. 4, pp. 258–264, Jun. 2008, doi: 10.1016/j.ndteint.2007.11.002.[2] S. Sotoudeh, F. Benedetto, S. Uzor, L. Lantini, K. Munisami, and F. Tosti, “A study into the integration of AR-based data collection and multi-dimensional signal processing methods for GB-SAR target detection,” in Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), M. Bilal and F. Tosti, Eds., SPIE, Aug. 2023, p. 49. doi: 10.1117/12.3007430.[3] F. Tosti, S. Adabi, L. Pajewski, G. Schettini, and A. Benedetto, “Large-scale analysis of dielectric and mechanical properties of pavement using GPR and LFWD,” in Proceedings of the 15th International Conference on Ground Penetrating Radar, IEEE, Jun. 2014, pp. 868–873. doi: 10.1109/ICGPR.2014.6970551.
Title: Investigating the Dynamic Behaviour of Civil Structures by Integration of Ground-Based Interferometric Radar and Augmented Reality 
Description:
Ensuring safety of civil infrastructure is a crucial goal in structural health monitoring (SHM).
Amongst the variety of monitoring sensors, the Ground-Based Interferometric Radar (GBIR) systems have recently gained attention for their advantages such as the very high resolution and fast data collection, as opposed to other conventional methods [1].
However, this technology suffers from precise target location when the acquisition is carried out in dynamic conditions.
For this purpose, external reflectors need to be installed in the portion of the structure under investigation, to which then the signal response is assumed to be related.
Considering this, the present research focuses on the investigation of the dynamic response of structures using GBIR aided with augmented reality (AR) [2].
AR assisted in controlling the position of the targets inside the radar’s beam of radiation and creating different acquisition scenarios in the same range based on a combination of their number and position.
Dynamic excitations were applied in the field using light weight deflectometer (LWD) [3], and their effects on the collected signal were investigated using empirical mode decomposition (EMD) signal processing technique across the different scenarios.
This allowed to have a better understanding of the signal response for multiple targets or at the boundaries of the signal footprint.
Results show that for data capturing using GBIR systems, AR can enhance the data quality by better controlling the collection phase.
In addition, the use of multi-dimensional signal processing techniques, such as the EMD, facilitated a more comprehensive understanding of the signal response in complex scenarios.
 Keywords: Structural health monitoring (SHM), Ground-based interferometric radar (GBIR), Augmented reality (AR), dynamic excitation, Empirical mode decomposition (EMD).
 AcknowledgementsThis research was funded by the Vice-Chancellor’s PhD Scholarship at the University of West London.
 References[1] M.
Pieraccini, M.
Fratini, F.
Parrini, C.
Atzeni, and G.
Bartoli, “Interferometric radar vs.
accelerometer for dynamic monitoring of large structures: An experimental comparison,” NDT and E International, vol.
41, no.
4, pp.
258–264, Jun.
2008, doi: 10.
1016/j.
ndteint.
2007.
11.
002.
[2] S.
Sotoudeh, F.
Benedetto, S.
Uzor, L.
Lantini, K.
Munisami, and F.
Tosti, “A study into the integration of AR-based data collection and multi-dimensional signal processing methods for GB-SAR target detection,” in Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), M.
Bilal and F.
Tosti, Eds.
, SPIE, Aug.
2023, p.
49.
doi: 10.
1117/12.
3007430.
[3] F.
Tosti, S.
Adabi, L.
Pajewski, G.
Schettini, and A.
Benedetto, “Large-scale analysis of dielectric and mechanical properties of pavement using GPR and LFWD,” in Proceedings of the 15th International Conference on Ground Penetrating Radar, IEEE, Jun.
2014, pp.
868–873.
doi: 10.
1109/ICGPR.
2014.
6970551.
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