Abstract
The electromagnetic imaging of multi-layered circular structures can be accomplished by means of different approaches. Among these approaches, the use of synthetic aperture radar (SAR) techniques with the compensation of the Green’s function for multi-layered circular cylinders provides a trade-off between accuracy and computational complexity. Nevertheless, this approach relies on measurement points acquired uniformly. Thus, this prevents the adoption of more flexible sampling schemes, limiting the use of inaccurate positioners or manual scanners. To overcome this limitation, this paper proposes a method to handle non-uniform cylindrically acquired data, enabling multi-layered circular imaging based on non-uniformly acquired measurements. For this purpose, the presented method starts by projecting the non-uniformly measured points onto different circles with equally-spaced points. After that, the Green’s function-based circular-SAR imaging method is applied to each projection circle. Lastly, the final SAR image is obtained by the superposition of the images from the previous step. Numerical simulations and experimental results demonstrated the effectiveness and robustness of the proposed method for practical nondestructive testing (NDT) applications.
Highlights
In the context of airborne synthetic aperture radar (SAR) imaging systems, circular scanning enables the acquisition of information from an object or a scene from multiple views, resulting in the approach known as circular-SAR (C-SAR) [1,2,3,4,5,6,7]
For many practical industrial applications based on C-SAR imaging, involving nondestructive testing (NDT) of layered dielectric structures, such as pipes made of plastics, fiberglass, high-density polyethylene (HDPE), and polyvinyl chloride (PVC) that carry fluids and chemicals, this assumption no longer holds
In order to characterize the theoretical performance of the method, the point spread function (PSF)
Summary
In the context of airborne synthetic aperture radar (SAR) imaging systems, circular scanning (i.e., circular synthetic aperture) enables the acquisition of information from an object or a scene from multiple views (angles), resulting in the approach known as circular-SAR (C-SAR) [1,2,3,4,5,6,7] In this remote sensing application, the free-space imaging background is usually assumed. In the case of -spaced data but inhomogeneous media, a SAR approach based on modeling field propagation by Green’s function for multi-layered geometries, implemented by efficient Wiener deconvolutions, has been demonstrated for NDT and imaging. Green’s function, once the non-uniform measurement points are known
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