Abstract
A Space-Time Turbo Bayesian Compressed Sensing (STTBCS) algorithm is proposed for Ultra-Wideband (UWB) systems in this paper. Based on the sparsity of UWB signals, the STTBCS algorithm provides an efficient approach for integrating spatial and temporal redundancies. A space-time structure is also designed for exploiting and transferring the spatial and temporal \emph{a priori} information for signal reconstructions in the framework of Bayesian Compressed Sensing (BCS). Simulation results using experimental UWB echo signals demonstrate that our STTBCS algorithm achieves good performance for UWB systems, compared with the traditional BCS and multitask BCS algorithms.
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