Abstract
In this paper, to deal with the concealed target detection problem, an accurate and efficient algorithm for near-field millimeter wave three-dimensional (3-D) imaging is proposed that uses a two-dimensional (2-D) plane antenna array. First, a two-dimensional fast Fourier transform (FFT) is performed on the scattered data along the antenna array plane. Then, a phase shift is performed to compensate for the spherical wave effect. Finally, fast Gaussian gridding based nonuniform FFT (FGG-NUFFT) combined with 2-D inverse FFT (IFFT) is performed on the nonuniform 3-D spatial spectrum in the frequency wavenumber domain to achieve 3-D imaging. The conventional method for near-field 3-D imaging uses Stolt interpolation to obtain uniform spatial spectrum samples and performs 3-D IFFT to reconstruct a 3-D image. Compared with the conventional method, our FGG-NUFFT based method is comparable in both efficiency and accuracy in the full sampled case and can obtain more accurate images with less clutter and fewer noisy artifacts in the down-sampled case, which are good properties for practical applications. Both simulation and experimental results demonstrate that the FGG-NUFFT-based near-field 3-D imaging algorithm can have better imaging performance than the conventional method for down-sampled measurements.
Highlights
In recent years, the demand for millimeter wave imaging techniques has increased in the field of nondestructive testing (NDT) or in security check applications since the threat of terrorism attacks is increasing [1,2,3,4,5]
Both simulation and experimental results demonstrate that the fast Gaussian gridding (FGG)-nonuniform fast Fourier transform (NUFFT)-based near-field 3-D imaging algorithm can have better imaging performance than the conventional method for down-sampled measurements
We investigate the effectiveness of the FGG-based NUFFT (FGG-NUFFT) method in near-field millimeter wave 3-D imaging and propose a FGG-NUFFT-based 3-D imaging method
Summary
The demand for millimeter wave imaging techniques has increased in the field of nondestructive testing (NDT) or in security check applications since the threat of terrorism attacks is increasing [1,2,3,4,5]. Conventional near-field 3-D holographic imaging methods [1,3] generally use 3-D interpolation to obtain uniform spatial spectrum samples and apply a 3-D fast Fourier transform to obtain the 3-D image of the target. These approaches can be considered interpolation-FFT methods, which would introduce interpolation errors and have a high demand for densely sampled data especially when the working frequency is high and the imaged scene is small, where the interpolation errors will be serious and greatly affect the quality of reconstructed images.
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