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The theory of compressed sensing has been applied to UWB systems for acquisition of UWB signals at a sub-Nyquist sampling rate. The UWB echo signal has lots of template redundancy which can be exploited to make the sparse UWB signal even sparser. This paper proposes a message passing Bayesian Compressed Sensing (BCS) algorithm to utilize the template redundancy for reducing the number of measurements and improving the capability of combating noise. Simulation results show the proposed massage passing BCS algorithm outperforms the original BCS and Orthogonal Matching Pursuit (OMP) algorithms.