Enhanced Adaptive Stagewise Orthogonal Matching Pursuit Algorithm Based on Compressed Sensing

The algorithms of the sparse signals reconstruction is the key issue in the theory of compressed sensing. The majority of greedy iterative-based algorithms only work under the condition of the prior known sparsity, which is hardly to be obtained accurately in real applications. An enhanced adaptive stagewise orthogonal matching pursuit algorithm is proposed in this paper. The proposed algorithm employs the backtracking and introduces an index parameter “I” based on the original threshold of the existing stagewise orthogonal matching pursuit algorithm, which can get the final support set more efficiently, obtaining better signal reconstruction. The simulation results show that, no matter whether the noise exists or not, the proposed algorithm can get better signal reconstruction quality with signal accurate reconstruction probability increased by 30%~40% without noise in measurement signals and MSE improved by 5~10dB averagely with noise in measurement signals, with less increase of computational complexity, as compared with other relevant algorithms.