Model-Based Multichannel Compressive Sampling with Ultra-Low Sampling Rate |
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Authors: | Yijiu Zhao Xiaoyan Zhuang Houjun Wang Zhijian Dai |
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Affiliation: | 1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China
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Abstract: | The emerging compressive sampling (CS) theory makes processing ultra-wide-band (UWB) signal at a low sampling rate possible if the underlying signal has a sparse representation in a certain basis. The feasibility of model based compressive sampling for ultra-wide-band (UWB) signal is investigated. In this paper, a multichannel compressive sampling architecture is developed to capture UWB signal at a rate much lower than Nyquist rate. The proposed framework considers sub-Nyquist sampling stream of delayed and weighted versions of a known signal with finite support in time domain. A basis function is constructed to realize sparse signal representation. To reduce the hardware cost, a segmented architecture is suggested. In addition, a joint signal recovery algorithm is presented. Experimental results indicate that, with this system, a UWB signal sampled at about 4% of Nyquist rate still can be recovered with overwhelming probability. |
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