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Fast Imaging Algorithm for Layered Dielectrics Based on Spatial Inhomogeneous Single-Input Single-Output Array
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DOI：10.1109/TGRS.2024.3468919.png)
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Abstract
En 中文
Array-based millimeter wave (MMW) holographic imaging technology has shown great application potential in nondestructive evaluation (NDE) of dielectric materials (such as composites). With the development of high-precision motion capture systems, the NDE of the internal structure of layered dielectric targets by handheld radar has become a new demand growth point. Since the elements of the handheld-radar-based array are randomly distributed in the 3-D space, the existing fast-imaging algorithms are difficult to be directly applied, which will restrict the development of this application. For this reason, this article proposes a fast-imaging algorithm for layered dielectric targets based on spatial 3-D nonuniform single-input single-output (SISO) array radar. The algorithm takes each element of the spatial 3-D random array as the center, expands it into a virtual uniform plane array, then transforms the echo data of the virtual array from the spatial domain to the wavenumber domain by using fast Fourier transform (FFT). After phase compensation, the wavenumber-domain data of all virtual arrays are added, to obtain the wavenumber-domain scattered echo data of the entire 3-D nonuniform SISO array radar. Finally, the imaging result of the target is obtained through the 2-D inverse Fourier transform (IFT) in azimuth direction and the segmented IFT in range direction. Numerical simulation and experimental measurements show that the proposed algorithm can significantly improve the imaging efficiency compared with the improved back-projection (IBP) algorithm which is also suitable for this scenario.
Keywords:
Layered dielectrics
spatial inhomogeneous single-input single-output (SISO) array
virtual uniform array
wavenumber domain superposition
Layered dielectrics
spatial inhomogeneous single-input single-output (SISO) array
virtual uniform array
wavenumber domain superposition
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