Abstract:

In the orthogonal matching pursuit ( OMP) algorithm based on compressive sensing,the selection of candidate atoms is very important to the final reconstruction performance. In this paper,a look ahead and backtrackingbased orthogonal matching pursuit ( LABOMP) algorithm is proposed by combining look ahead procedures with the backtracking strategy to update a candidate atom set. In this algorithm,all the iterations are divided into early and upper stages. At the former,the optimal atom is selected by forecasting its final performance in the future iterations,while at the latter,the backtracking strategy is introduced,and a previous wrongly-selected atom is then eliminated once per two iterations. Experimental results show that the proposed LABOMP algorithm is applicable and effective; and that its average exact reconstruction probability for Gaussian or binary sparse signals is respectively 12.5% or 18.2% higher than that of LAOMP ( Look Ahead Orthogonal Matching Pursuit) algorithm at the upper stage because the backtracking strategy overcomes the disadvantage of LAOMP algorithm.

Key words: compressive sensing, signal reconstruction, orthogonal matching pursuit, look ahead prediction, backtracking strategy