Radioheliographs can obtain solar images at high temporal and spatial resolution,with a high dynamic range.These are among the most important instruments for studying solar radio bursts,understanding solar eruption ev...Radioheliographs can obtain solar images at high temporal and spatial resolution,with a high dynamic range.These are among the most important instruments for studying solar radio bursts,understanding solar eruption events,and conducting space weather forecasting.This study aims to explore the effective use of radioheliographs for solar observations,specifically for imaging coronal mass ejections(CME),to track their evolution and provide space weather warnings.We have developed an imaging simulation program based on the principle of aperture synthesis imaging,covering the entire data processing flow from antenna configuration to dirty map generation.For grid processing,we propose an improved non-uniform fast Fourier transform(NUFFT)method to provide superior image quality.Using simulated imaging of radio coronal mass ejections,we provide practical recommendations for the performance of radioheliographs.This study provides important support for the validation and calibration of radioheliograph data processing,and is expected to profoundly enhance our understanding of solar activities.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
Sparse-view x-ray computed tomography （CT） imaging is an interesting topic in CT field and can efficiently decrease radiation dose. Compared with spatial reconstruction, a Fourier-based algorithm has advantages in r...Sparse-view x-ray computed tomography （CT） imaging is an interesting topic in CT field and can efficiently decrease radiation dose. Compared with spatial reconstruction, a Fourier-based algorithm has advantages in reconstruction speed and memory usage. A novel Fourier-based iterative reconstruction technique that utilizes non-uniform fast Fourier transform （NUFFF） is presented in this work along with advanced total variation （TV） regularization for a fan sparse-view CT. The proposition of a selective matrix contributes to improve reconstruction quality. The new method employs the NUFFT and its adjoin to iterate back and forth between the Fourier and image space. The performance of the proposed algorithm is demonstrated through a series of digital simulations and experimental phantom studies. Results of the proposed algorithm are compared with those of existing TV-regularized techniques based on compressed sensing method, as well as basic algebraic reconstruction technique. Compared with the existing TV-regularized techniques, the proposed Fourier-based technique significantly improves convergence rate and reduces memory allocation, respectively.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
Long-term coherent integration can remarkably improve the ability of detection and motion parameter estimation of radar for maneuvering targets.However,the linear range migration,quadratic range migration(QRM),and Dop...Long-term coherent integration can remarkably improve the ability of detection and motion parameter estimation of radar for maneuvering targets.However,the linear range migration,quadratic range migration(QRM),and Doppler frequency migration within the coherent processing interval seriously degrade the detection and estimation performance.Therefore,an efficient and noise-resistant coherent integration method based on location rotation transform(LRT)and non-uniform fast Fourier transform(NuFFT)is proposed.QRM is corrected by the second-order keystone transform.Using the relationship between the rotation angle and Doppler frequency,a novel phase compensation function is constructed.Motion parameters can be rapidly estimated by LRT and NuFFT.Compared with several representative algorithms,the proposed method achieves a nearly ideal detection performance with low computational cost.Finally,experiments based on measured radar data are conducted to verify the proposed algorithm.展开更多
Ewald summation method, based on Non-Uniform FFTs (ENUF) to compute the electrostatic interactions and forces, is implemented in two different particle simulation schemes to model molecular and soft matter, in classic...Ewald summation method, based on Non-Uniform FFTs (ENUF) to compute the electrostatic interactions and forces, is implemented in two different particle simulation schemes to model molecular and soft matter, in classical all-atom Molecular Dynamics and in Dissipative Particle Dynamics for coarse-grained particles. The method combines the traditional Ewald method with a non-uniform fast Fourier transform library (NFFT), making it highly efficient. It scales linearly with the number of particles as , while being both robust and accurate. It conserves both energy and the momentum to float point accuracy. As demonstrated here, it is straight- forward to implement the method in existing computer simulation codes to treat the electrostatic interactions either between point-charges or charge distributions. It should be an attractive alternative to mesh-based Ewald methods.展开更多
针对具有任意阶运动的目标的长时间相参积累问题,提出一种基于多维非均匀快速傅里叶变换(non-uniform fast Fourier transform,NUFFT)的长时间相参积累算法。该算法先在快时间频域沿慢时间维利用多维NUFFT实现运动补偿,然后通过快速傅...针对具有任意阶运动的目标的长时间相参积累问题,提出一种基于多维非均匀快速傅里叶变换(non-uniform fast Fourier transform,NUFFT)的长时间相参积累算法。该算法先在快时间频域沿慢时间维利用多维NUFFT实现运动补偿,然后通过快速傅里叶逆变换(inverse fast Fourier transform,IFFT)最终实现相参积累。该算法积累性能接近理论最优且计算量小于已有算法。特别地,对于具有加加速度的运动目标进一步提出基于Wigner-NUFFT的相参积累算法,该算法相比多维NUFFT,计算量大大减小,但对积累前单个脉冲的信噪比提出更高要求。仿真结果证明了所提算法的有效性。展开更多
基金supported by the grants of National Natural Science Foundation of China(42374219,42127804)the Qilu Young Researcher Project of Shandong University.
文摘Radioheliographs can obtain solar images at high temporal and spatial resolution,with a high dynamic range.These are among the most important instruments for studying solar radio bursts,understanding solar eruption events,and conducting space weather forecasting.This study aims to explore the effective use of radioheliographs for solar observations,specifically for imaging coronal mass ejections(CME),to track their evolution and provide space weather warnings.We have developed an imaging simulation program based on the principle of aperture synthesis imaging,covering the entire data processing flow from antenna configuration to dirty map generation.For grid processing,we propose an improved non-uniform fast Fourier transform(NUFFT)method to provide superior image quality.Using simulated imaging of radio coronal mass ejections,we provide practical recommendations for the performance of radioheliographs.This study provides important support for the validation and calibration of radioheliograph data processing,and is expected to profoundly enhance our understanding of solar activities.
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Projected supported by the National High Technology Research and Development Program of China(Grant No.2012AA011603)the National Natura Science Foundation of China(Grant No.61372172)
文摘Sparse-view x-ray computed tomography （CT） imaging is an interesting topic in CT field and can efficiently decrease radiation dose. Compared with spatial reconstruction, a Fourier-based algorithm has advantages in reconstruction speed and memory usage. A novel Fourier-based iterative reconstruction technique that utilizes non-uniform fast Fourier transform （NUFFF） is presented in this work along with advanced total variation （TV） regularization for a fan sparse-view CT. The proposition of a selective matrix contributes to improve reconstruction quality. The new method employs the NUFFT and its adjoin to iterate back and forth between the Fourier and image space. The performance of the proposed algorithm is demonstrated through a series of digital simulations and experimental phantom studies. Results of the proposed algorithm are compared with those of existing TV-regularized techniques based on compressed sensing method, as well as basic algebraic reconstruction technique. Compared with the existing TV-regularized techniques, the proposed Fourier-based technique significantly improves convergence rate and reduces memory allocation, respectively.
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.
基金the National Natural Science Foundation of China(No.61501513)。
文摘Long-term coherent integration can remarkably improve the ability of detection and motion parameter estimation of radar for maneuvering targets.However,the linear range migration,quadratic range migration(QRM),and Doppler frequency migration within the coherent processing interval seriously degrade the detection and estimation performance.Therefore,an efficient and noise-resistant coherent integration method based on location rotation transform(LRT)and non-uniform fast Fourier transform(NuFFT)is proposed.QRM is corrected by the second-order keystone transform.Using the relationship between the rotation angle and Doppler frequency,a novel phase compensation function is constructed.Motion parameters can be rapidly estimated by LRT and NuFFT.Compared with several representative algorithms,the proposed method achieves a nearly ideal detection performance with low computational cost.Finally,experiments based on measured radar data are conducted to verify the proposed algorithm.
文摘Ewald summation method, based on Non-Uniform FFTs (ENUF) to compute the electrostatic interactions and forces, is implemented in two different particle simulation schemes to model molecular and soft matter, in classical all-atom Molecular Dynamics and in Dissipative Particle Dynamics for coarse-grained particles. The method combines the traditional Ewald method with a non-uniform fast Fourier transform library (NFFT), making it highly efficient. It scales linearly with the number of particles as , while being both robust and accurate. It conserves both energy and the momentum to float point accuracy. As demonstrated here, it is straight- forward to implement the method in existing computer simulation codes to treat the electrostatic interactions either between point-charges or charge distributions. It should be an attractive alternative to mesh-based Ewald methods.
文摘针对具有任意阶运动的目标的长时间相参积累问题,提出一种基于多维非均匀快速傅里叶变换(non-uniform fast Fourier transform,NUFFT)的长时间相参积累算法。该算法先在快时间频域沿慢时间维利用多维NUFFT实现运动补偿,然后通过快速傅里叶逆变换(inverse fast Fourier transform,IFFT)最终实现相参积累。该算法积累性能接近理论最优且计算量小于已有算法。特别地,对于具有加加速度的运动目标进一步提出基于Wigner-NUFFT的相参积累算法,该算法相比多维NUFFT,计算量大大减小,但对积累前单个脉冲的信噪比提出更高要求。仿真结果证明了所提算法的有效性。
