A Butterfly Algorithm for Synthetic Aperture Radar Imaging

被引:31
作者
Demanet, Laurent [1 ]
Ferrara, Matthew [2 ]
Maxwell, Nicholas [3 ]
Poulson, Jack [4 ]
Ying, Lexing [4 ,5 ]
机构
[1] MIT, Dept Math, Cambridge, MA 02139 USA
[2] Matrix Res Inc, Dayton, OH 45432 USA
[3] Univ Houston, Dept Math, Houston, TX 77204 USA
[4] Univ Texas Austin, ICES, Austin, TX 78712 USA
[5] Univ Texas Austin, Dept Math, Austin, TX 78712 USA
基金
美国国家科学基金会;
关键词
fast algorithms; low-rank expansions; backprojection; synthetic aperture radar; DECOMPOSITION ALGORITHM; FOURIER-TRANSFORM; SCATTERING; RECONSTRUCTION; COMPUTATION;
D O I
10.1137/100811593
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In spite of an extensive literature on fast algorithms for synthetic aperture radar (SAR) imaging, it is not currently known if it is possible to accurately form an image from N data points in provable near-linear time complexity. This paper seeks to close this gap by proposing an algorithm which runs in complexity O(N logN log(1/epsilon)) without making the far-field approximation or imposing the beam pattern approximation required by time-domain backprojection, with epsilon the desired pixelwise accuracy. It is based on the butterfly scheme, which unlike the FFT works for vastly more general oscillatory integrals than the discrete Fourier transform. A complete error analysis is provided: the rigorous complexity bound has additional powers of logN and log(1/epsilon) that are not observed in practice.
引用
收藏
页码:203 / 243
页数:41
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