研究推导了安检系统近场信号传播方程,并引入了一维近场响应矩阵,在此基础上,提出了结合LMS(Least Mean Square,LMS)自适应波束形成的非均匀快速傅里叶变换(Non-uniform Fast Fourier Transform,NUFFT)二维近场成像算法。先对多阵元接...研究推导了安检系统近场信号传播方程,并引入了一维近场响应矩阵,在此基础上,提出了结合LMS(Least Mean Square,LMS)自适应波束形成的非均匀快速傅里叶变换(Non-uniform Fast Fourier Transform,NUFFT)二维近场成像算法。先对多阵元接收信号进行自适应波束形成处理,再通过NUFFT重构目标图像。对文中算法与传统的波束形成NUFFT二维成像算法进行了模拟仿真比较分析,仿真结果表明,提出的算法具有更好的噪声抑制效果,提高了毫米波近场成像的质量。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
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
文摘研究推导了安检系统近场信号传播方程,并引入了一维近场响应矩阵,在此基础上,提出了结合LMS(Least Mean Square,LMS)自适应波束形成的非均匀快速傅里叶变换(Non-uniform Fast Fourier Transform,NUFFT)二维近场成像算法。先对多阵元接收信号进行自适应波束形成处理,再通过NUFFT重构目标图像。对文中算法与传统的波束形成NUFFT二维成像算法进行了模拟仿真比较分析,仿真结果表明,提出的算法具有更好的噪声抑制效果,提高了毫米波近场成像的质量。
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).
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.
