This paper applies a 3-D nonuniform fast Fourier transform(NUFFT)migration method to image both free-space and buried targets from data collected by a ultra-wideband ground penetrating radar(GPR)system.The method inco...This paper applies a 3-D nonuniform fast Fourier transform(NUFFT)migration method to image both free-space and buried targets from data collected by a ultra-wideband ground penetrating radar(GPR)system.The method incorporates the NUFFT algorithm into 3-D phase shift migration to evaluate the inverse Fourier transform more accurately and more efficiently than the conventional migration methods.Previously,the nonuniform nature of the wavenumber space required linear interpolation before the regular fast Fourier transform(FFT)could be applied.However,linear interpolation usually degrades the quality of reconstructed images.The NUFFT method mitigates such errors by using high-order spatial-varying kernels.The NUFFT migration method is utilized to reconstruct GPR images collected in laboratory.A plywood sheet in free space and a buried plexiglas chamber are successfully reconstructed.The results in 3-D visualization demonstrate the outstanding performance of the method to retrieve the geometry of the objects.Several buried landmines are also scanned and reconstructed using this method.Since the images resolve the features of the objects well,they can be utilized to assist the landmine discrimination.展开更多
针对超声衍射层析成像传统采用的双线性插值法重建精度不高的问题,提出一种高精度的核卷积插值重建算法.首先,根据标准的sheep and Logan体模算出重建数据点的值,再选用最小二乘非均匀快速傅里叶变换(LS-NUFFT)算法里的核矩阵作为卷积核...针对超声衍射层析成像传统采用的双线性插值法重建精度不高的问题,提出一种高精度的核卷积插值重建算法.首先,根据标准的sheep and Logan体模算出重建数据点的值,再选用最小二乘非均匀快速傅里叶变换(LS-NUFFT)算法里的核矩阵作为卷积核,并用此核矩阵将非笛卡儿分布的重建数据点插值到笛卡儿网格内,最后用二维的傅里叶逆变换完成图像的重建.与双线性插值法和高斯核卷积法相比较,LS-NUFFT核矩阵法所得重建图像的2-范数误差比双线性法减少了40%以上,重建时间比高斯核卷积法减少约50%.展开更多
A near-field three-dimensional(3 D)imaging method combining multichannel joint sparse recovery(MJSR)and fast Gaussian gridding nonuniform fast Fourier transform(FGGNUFFT)is proposed,based on a perfect combination of t...A near-field three-dimensional(3 D)imaging method combining multichannel joint sparse recovery(MJSR)and fast Gaussian gridding nonuniform fast Fourier transform(FGGNUFFT)is proposed,based on a perfect combination of the compressed sensing(CS)theory and the matched filtering(MF)technique.The approach has the advantages of high precision and high efficiency:multichannel joint sparse constraint is adopted to improve the problem that the images recovered by the single channel imaging algorithms do not necessarily share the same positions of the scattering centers;the CS dictionary is constructed by combining MF and FGG-NUFFT,so as to improve the imaging efficiency and memory requirement.Firstly,a near-field 3 D imaging model of joint sparse recovery is constructed by combining the MF-based imaging method.Secondly,FGG-NUFFT and reverse FGG-NUFFT are used to replace the interpolation and Fourier transform in MF-based imaging methods,and a sensing matrix with high precision and high efficiency is constructed according to the traditional imaging process.Thirdly,a fast imaging recovery is performed by using the improved separable surrogate functionals(SSF)optimization algorithm,only with matrix and vector multiplication.Finally,a 3 D imagery of the near-field target is obtained by using both the horizontal and the pitching interferometric phase information.This paper contains two imaging models,the only difference is the sub-aperture method used in inverse synthetic aperture radar(ISAR)imaging.Compared to traditional CS-based imaging methods,the proposed method includes both forward transform and inverse transform in each iteration,which improves the quality of reconstruction.The experimental results show that,the proposed method improves the imaging accuracy by about O(10),accelerates the imaging speed by five times and reduces the memory usage by about O(10~2).展开更多
基金supported by a DARPA/ARO MURI grant DAAD19-02-1-0252NSF through grant CCR-0219528National Institute of Health under grant number 5R21CA114680-02.
文摘This paper applies a 3-D nonuniform fast Fourier transform(NUFFT)migration method to image both free-space and buried targets from data collected by a ultra-wideband ground penetrating radar(GPR)system.The method incorporates the NUFFT algorithm into 3-D phase shift migration to evaluate the inverse Fourier transform more accurately and more efficiently than the conventional migration methods.Previously,the nonuniform nature of the wavenumber space required linear interpolation before the regular fast Fourier transform(FFT)could be applied.However,linear interpolation usually degrades the quality of reconstructed images.The NUFFT method mitigates such errors by using high-order spatial-varying kernels.The NUFFT migration method is utilized to reconstruct GPR images collected in laboratory.A plywood sheet in free space and a buried plexiglas chamber are successfully reconstructed.The results in 3-D visualization demonstrate the outstanding performance of the method to retrieve the geometry of the objects.Several buried landmines are also scanned and reconstructed using this method.Since the images resolve the features of the objects well,they can be utilized to assist the landmine discrimination.
文摘针对超声衍射层析成像传统采用的双线性插值法重建精度不高的问题,提出一种高精度的核卷积插值重建算法.首先,根据标准的sheep and Logan体模算出重建数据点的值,再选用最小二乘非均匀快速傅里叶变换(LS-NUFFT)算法里的核矩阵作为卷积核,并用此核矩阵将非笛卡儿分布的重建数据点插值到笛卡儿网格内,最后用二维的傅里叶逆变换完成图像的重建.与双线性插值法和高斯核卷积法相比较,LS-NUFFT核矩阵法所得重建图像的2-范数误差比双线性法减少了40%以上,重建时间比高斯核卷积法减少约50%.
基金supported by the National Natural Science Foundation of China(61771369 61775219+5 种基金 61640422)the Fundamental Research Funds for the Central Universities(JB180310)the Equipment Research Program of the Chinese Academy of Sciences(YJKYYQ20180039)the Shaanxi Provincial Key R&D Program(2018SF-409 2018ZDXM-SF-027)the Natural Science Basic Research Plan
文摘A near-field three-dimensional(3 D)imaging method combining multichannel joint sparse recovery(MJSR)and fast Gaussian gridding nonuniform fast Fourier transform(FGGNUFFT)is proposed,based on a perfect combination of the compressed sensing(CS)theory and the matched filtering(MF)technique.The approach has the advantages of high precision and high efficiency:multichannel joint sparse constraint is adopted to improve the problem that the images recovered by the single channel imaging algorithms do not necessarily share the same positions of the scattering centers;the CS dictionary is constructed by combining MF and FGG-NUFFT,so as to improve the imaging efficiency and memory requirement.Firstly,a near-field 3 D imaging model of joint sparse recovery is constructed by combining the MF-based imaging method.Secondly,FGG-NUFFT and reverse FGG-NUFFT are used to replace the interpolation and Fourier transform in MF-based imaging methods,and a sensing matrix with high precision and high efficiency is constructed according to the traditional imaging process.Thirdly,a fast imaging recovery is performed by using the improved separable surrogate functionals(SSF)optimization algorithm,only with matrix and vector multiplication.Finally,a 3 D imagery of the near-field target is obtained by using both the horizontal and the pitching interferometric phase information.This paper contains two imaging models,the only difference is the sub-aperture method used in inverse synthetic aperture radar(ISAR)imaging.Compared to traditional CS-based imaging methods,the proposed method includes both forward transform and inverse transform in each iteration,which improves the quality of reconstruction.The experimental results show that,the proposed method improves the imaging accuracy by about O(10),accelerates the imaging speed by five times and reduces the memory usage by about O(10~2).
