Improved sparse signal recovery method based on matching pursuit revised MAP estimation
The problem of recovering a sparse signal buried in noise from a linear observing system has been studied, via utilising statistic prior information of noise and signal, a fast matching pursuit revised maximum a posterior (MP-RMAP) estimation method is proposed. The proposed method overcomes the none-robust estimation problem that fast Bayesian matching pursuit has in high signal-to-noise ratio cases. Compared with other methods, the MP-RMAP method is able to improve the estimation accuracy with low complexity. Experimental results verify the validity of the proposed algorithm.
