Abstract
The random equivalent sampling (RES) is a well-known sampling technique that can be used to capture a high-speed repetitive waveform with low sampling rate. In this paper, the feasibility of spectrum-blind multiband signal reconstruction for data sampled from RES is investigated. We propose a RES sampling pattern and its corresponding mathematical model that guarantees well-conditioned reconstruction of multiband signal with unknown spectral support. We give the minimum number of RES acquisitions that hold overwhelming probability to successfully reconstruct original signal. We demonstrate that for signal with specific spectral occupation, the minimum number of RES acquisitions and the minimum sampling rate could be approached. The signal reconstruction is studied in the framework of compressive sampling theory. The eigen-decomposition and minimum description length criteria are adopted to adaptively estimate the dimension of signal, and the number of unknowns of reconstruction problem is reduced. Experimental results are reported to indicate that, for a spectrum-blind sparse multiband signal, the proposed reconstruction algorithm for RES is feasible and robust.
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Acknowledgments
This work is supported in part by the National Natural Science Foundation of China (Grant No. 61301264), in part by the Ph.D. Programs Foundation of Ministry of Education of China (Grant No. 20130185120019), and in part by the Fundamental Research Funds for the Central Universities (Grant No. ZYGX2013J089).
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Zhao, Y., Wang, L., Wang, H. et al. Minimum Rate Sampling and Spectrum-Blind Reconstruction in Random Equivalent Sampling. Circuits Syst Signal Process 34, 2667–2680 (2015). https://doi.org/10.1007/s00034-015-9989-4
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DOI: https://doi.org/10.1007/s00034-015-9989-4