Hongxia Bu

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To achieve high-resolution images, synthetic aperture radar (SAR) faces considerable technical challenges such as huge amount of data samples and high hardware complexity. Compressed sensing (CS) theory shows that the super-resolved images can be reconstructed from an extremely smaller set of measurements than what is generally considered necessary by(More)
Compressed sensing (CS) is a new technique of utilizing a priori knowledge on sparsity of data in a certain domain for minimizing necessary number of measurements. Based on this idea, this paper proposes a novel synthetic aperture radar (SAR) imaging approach by exploiting sparseness of echo data in the fractional Fourier domain. The effectiveness and(More)
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