How to cite:
Liao, X.; Jin, C.; Liu, Z. Compressed Sensing Imaging for Staggered SAR with Low Oversampling Rate. Preprints2020, 2020100444. https://doi.org/10.20944/preprints202010.0444.v1
Liao, X.; Jin, C.; Liu, Z. Compressed Sensing Imaging for Staggered SAR with Low Oversampling Rate. Preprints 2020, 2020100444. https://doi.org/10.20944/preprints202010.0444.v1
Liao, X.; Jin, C.; Liu, Z. Compressed Sensing Imaging for Staggered SAR with Low Oversampling Rate. Preprints2020, 2020100444. https://doi.org/10.20944/preprints202010.0444.v1
APA Style
Liao, X., Jin, C., & Liu, Z. (2020). Compressed Sensing Imaging for Staggered SAR with Low Oversampling Rate. Preprints. https://doi.org/10.20944/preprints202010.0444.v1
Chicago/Turabian Style
Liao, X., Changlin Jin and Zhe Liu. 2020 "Compressed Sensing Imaging for Staggered SAR with Low Oversampling Rate" Preprints. https://doi.org/10.20944/preprints202010.0444.v1
Abstract
This paper focuses on processing low oversampling echo data of staggered synthetic aperture radar (SAR). In staggered mode, the non-uniformly sampling and irregular loss of echo data cause azimuth ambiguity which severely degrades the imaging quality. To solve this problem, we propose a compressed sensing (CS) method in which the non-uniform fast Fourier transform (NUFFT) technique is adopted to obtain uniform azimuth spectrum, and the fast iterative shrinkage thresholding algorithm (FISTA) is utilized to efficiently reconstruct the ambiguity-free image from in-complete echo data. Simulation results demonstrate the proposed method can effectively suppress the azimuth ambiguity in the vicinity of targets.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
