A Study on Millimeter Wave SAR Imaging for Non-Destructive Testing of Rebar in Reinforced Concrete

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 20; p. 8030
• Main Authors: Pham, The-Hien, Kim, Kil-Hee, Hong, Ic-Pyo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 20.10.2022; MDPI
• Subjects: Algorithms; Artificial satellites in remote sensing; compressed sensing; Concrete; Continuous radiation; Data collection; Digital signal processors; Frequency ranges; Image quality; Imaging systems; Methods; millimeter wave; Millimeter waves; non-destructive testing; Nondestructive testing; Radar; Radar data; Radar imaging; Rebar; Reinforced concrete; SAR imaging; Sensors; Signal processing; Solvers; Synthetic aperture radar
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22208030

In this study, we investigate a millimeter wave (mmWave) synthetic aperture radar (SAR) imaging scheme utilizing a low-cost frequency modulated continuous wave (FMCW) radar to take part in non-destructive testing which could be a useful tool for both civilian and military demands. The FMCW radar working in the frequency range from 76 GHz to 81 GHz is equipped with a 2-D moving platform aiming to reconstruct the 2-D image of the shape of the target object. Due to the lab environment containing several devices and furniture, various noise and interference signals from the floor are not avoidable. Therefore, the digital signal processing algorithms are joined to remove the undesired signals as well as improve the target recognition. This study adopts the range migration algorithms (RMAs) on the processed reflected signal data to form the image of the target because of its verified ability in this type of mission. On the other hand, the integration of compressed sensing (CS) algorithms into the SAR imaging system is also researched which helps to improve the performance of the system by reducing the measurement duration while still maintaining the image quality. Three minimization algorithms are used involving the imaging system as the CS solvers reconstruct the radar data before being processed by RMA to form the image. The proposed imaging scheme demonstrates its good ability with high azimuth resolution in the mission of detecting tiny cracks in the rebar of reinforced concrete. In addition, the participation of CS algorithms improves the performance of the scheme as the cracks on the rebar can be located on the images, which are reconstructed from only 30% of the dataset. The comparison of CS solvers shows that ADMM outperforms the other candidates in the reconstruction task.