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In this paper, we propose the exploitation of sparse Bayesian learning in multiple-input multiple-output (MIMO) systems to account for the multi-dimensional group sparse nature of extended defects in guided ultrasonic wave based structural health monitoring. The multi-dimensional group sparsity in the underlying reconstruction problems arises due to the clustered spatial occupancy of extended defects...
In through-the-wall radar imaging applications, exploitation of group sparsity of the targets under multipath propagation allows high-resolution ghost-free imaging. However, such multipath exploitation schemes may suffer from imperfect knowledge of the surrounding scatterers, such as interior walls. In this paper, a novel two-stage Bayesian compressive sensing approach is proposed for joint scene...
In this paper, a novel modified complex multi-task Bayesian compressive sensing (MCMT-BCS) algorithm is proposed to acquire high-resolution images in stepped-frequency through-the-wall radar imaging (TWRI) exploiting multipath. Unlike traditional TWRI approaches that assume frequency-independent scattering model, we develop a practical subband scattering model to characterize real-world scattering...
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