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A Novel SAR Imaging Algorithm Based on Compressed Sensing
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DOI：10.1109/LGRS.2014.2372319.png)
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摘要
En 中文
To reduce the amount of measurements, compressed sensing (CS) has been introduced to synthetic aperture radar (SAR). In this letter, a novel CS-SAR imaging algorithm is proposed, which consists of 2-D undersampling, range reconstruction, range-azimuth decoupling, and azimuth reconstruction. In the proposed algorithm, the range profile is reconstructed in the fractional Fourier domain, and range-azimuth decoupling in the case of azimuth undersampling is realized by using the reference function multiplication and chirp-z transform. Comparisons with the existing 2-D undersampling CS-SAR imaging algorithms are also presented. Experimental results from both simulated and real data demonstrate that the proposed algorithm can efficiently realize high-quality imaging with limited measurements.
Keyword:
Chirp-z transform (CZT)
compressed sensing (CS)
dechirp
fractional Fourier transform (FRFT)
synthetic aperture radar (SAR)
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16.4
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被引数:
5.1K
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