利用稀疏非负矩阵分解的大转角SAR成像方法

doi:10.3969/j.issn.1001-2400.2014.03.008

Abstract

Abstract:

This paper proposes a novel WASAR imaging scheme, which divides the full aperture data into several overlapping sub-apertures and uses the Polar Format Algorithm (PFA) to obtain sub-images at different aspects. Finally we perform full aperture image composition via Non-negative Matrix Factorization (NMF) with a sparse regularization term. The target feature of the synthesized image is enhanced and the SNR is improved. Simulation results verify the effectiveness of the novel approach.

Key words: synthetic aperture radar(SAR), non-negative matrix factorization(NMF), sparseness, sub-aperture, image fusion

CLC Number:

TN957

XU Ran;LI Yachao;XING Mengdao. Wide angle SAR imaging via sparse non-negative matrix factorization[J].J4, 2014, 41(3): 49-55.

References

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Wide angle SAR imaging via sparse non-negative matrix factorization

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