Imaging sparse scatterers through a multi-frequency CS approach
Antennas and Propagation（2014）
摘要
In this paper an inverse scattering technique based on the multi-task Bayesian Compressive Sensing is presented within a multi-frequency framework. After recasting the problem in a probabilistic sense, the solution to the imaging problem is determined by means of an efficient Relevant Vector Machine coupled with a contrast source inversion procedure. Selected numerical results are discussed to assess and compare the efficiency and robustness of the proposed strategy with respect to the state-of-the-art techniques.
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关键词
bayes methods,compressed sensing,electrical engineering computing,electromagnetic wave scattering,probability,support vector machines,contrast source inversion procedure,imaging sparse scatterers,inverse scattering technique,multifrequency cs approach,multifrequency framework,multitask bayesian compressive sensing,relevant vector machine,multi-task bayesian compressive sampling,inverse scattering,multi-frequency microwave imaging,dielectrics,image reconstruction,antennas,imaging,signal to noise ratio
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