title: Multiband signal reconstruction for random equivalent sampling.
abstract: The random equivalent sampling (RES) is a sampling approach that can be applied to capture high speed repetitive signals with a sampling rate that is much lower than the Nyquist rate. However, the uneven random distribution of the time interval between the excitation pulse and the signal degrades the signal reconstruction performance. For sparse multiband signal sampling, the compressed sensing (CS) based signal reconstruction algorithm can tease out the band supports with overwhelming probability and reduce the impact of uneven random distribution in RES. In this paper, the mathematical model of RES behavior is constructed in the frequency domain. Based on the constructed mathematical model, the band supports of signal can be determined. Experimental results demonstrate that, for a signal with unknown sparse multiband, the proposed CS-based signal reconstruction algorithm is feasible, and the CS reconstruction algorithm outperforms the traditional RES signal reconstruction method.
authors.affiliation: School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors.forename: Y J
authors.initials: YJ
authors.lastname: Zhao
authors.affiliation: School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors.forename: C J
authors.initials: CJ
authors.lastname: Liu