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By exploiting the sparsity of the imaging scene, compressed sensing(CS) imaging may provide an effective solution to cope with the tradeoff of high azimuth resolution and wide swath in synthetic aperture sonar imaging. However, existing CS imaging methods are based on narrowband signal model and the scaling effect on the echoes is normally omitted, which may seriously affect the ultimate image reconstruction performance.This paper establishes the wideband CS underwater sonar imaging model at first, where the scaling effect and Doppler frequency shift are jointly considered. Furthermore, two wideband CS imaging approaches are discussed in uniform scale-range space and velocity-range space, respectively. Besides, modified l1-norm minimization algorithms are proposed for the scene reconstruction in velocity-range space. Finally, numerical experiments are provided to demonstrate the effectiveness of the proposed model and the reconstruction algorithms.
However, existing CS imaging methods are based on narrowband signal model and the scaling effect on the echoes is normally omitted, which may seriously affect the ultimate image reconstruction performance. This paper establishes the wideband CS underwater sonar imaging model at first, where the scaling effect and Doppler frequency shift are jointly considered. CS imaging approaches are discussed in uniform scale-range space and velocity-range space, respectively. Modified l1-norm minimization algorithms are proposed for the scene reconstruction in velocity-range space. Finally, numerical experiments are provided to demonstrate the effectiveness of the proposed model and the reconstruction algorithms.