Block compressive sensing in Synthetic Aperture Radar (SAR)

Kazemi, Peyman; Modarres-Hashemi, Mahmoud; Naghsh, Mohammad Mahdi

doi:10.1109/iraniancee.2016.7585726

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…The appearance of CS in the previous two decades [ 21 , 22 ] has brought many CS-based potential applications not only for image processing but also for signal processing, and SAR imaging is also one of the candidates [ 23 , 24 ]. The author in [ 25 ] proposed an intensity-hue-saturation-based (IHS-based) pan-sharpening method using ripplet transform and CS to solve the evident spectral distortion problem caused by the IHS transform.…”

Section: Introductionmentioning

confidence: 99%

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

Hien

Kim

Hong

2022

Sensors

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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.

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