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
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 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).
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。
