The existing recovery algorithm of modulated wideband converter (MWC)-based sub-Nyquist sampling is far from satisfactory.Aiming at this problem

a recovery algorithm for MWC based on random projection method is proposed.This algorithm projects the measurement value matrix of MWC onto a random matrix with lower dimension to form a new measurement value matrix

and then solves a multiple measurement vector problem using a solver proposed.The recovery performance is enhanced through examining and repeating the tentative solving processes.This paper validates the effectiveness of the algorithm from both theoretical and experimental perspectives.Numerical experiments demonstrate that

compared with the popular ReMBo algorithm

the proposed algorithm significantly improves the success rate of recovery.From the same number of channels a signal with more spectral bands can be recovered by this algorithm

and a signal with the same number of bands can be recovered using fewer channels.Furthermore

the run time of this algorithm does not increase greatly.In contrast

compared with ReMBo

this algorithm can use a lower time cost to achieve a higher recovery performance when the spectral bands of the signal exceed a specific number.