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Sparse signal processing is a signal processing technique that takes advantage of signal’s sparsity,allowing signal to be recovered with a reduced number of samples.Compressive sensing,a new branch of the sparse signal processing,has become a rapidly growing research field.Sparse microwave imaging introduces the sparse signal processing theory to radar imaging to obtain new theories,new systems and new methodologies of microwave imaging.This paper first summarizes the latest application of sparse microwave imaging,including Synthetic Aperture Radar(SAR),tomographic SAR and inverse SAR.As sparse signal processing keeps evolving,an avalanche of results have been obtained.We also highlight its recent theoretical advances,including structured sparsity,off-grid,Bayesian approaches,and point out new research directions in sparse microwave imaging.
Sparse signal processing is a signal processing technique that takes advantage of signal’s sparsity, allowing signal to be recovered with a reduced number of samples. Compressive sensing, a new branch of the sparse signal processing, has become a rapidly growing research field. Sparse microwave imaging introduces the sparse signal processing theory to radar imaging to obtain new theories, new systems and new methodologies of microwave imaging. This paper first summarizes the latest application of sparse microwave imaging, including Synthetic Aperture Radar (SAR), tomographic SAR and inverse SAR. As sparse signal processing keeps evolving, an avalanche of results have been obtained. We also highlight its recent theoretical advances, including structured sparsity, off-grid, Bayesian approaches, and point out new research directions in sparse microwave imaging.