  Recently, many practical algorithms have been proposed to recover the sparse
signal from fewer measurements. Orthogonal matching pursuit (OMP) is one of the
most effective algorithm. In this paper, we use the restricted isometry
property to analysis the algorithm. We show that, under certain conditions
based on the restricted isometry property and the signals, OMP will recover the
support of the sparse signal when measurements are corrupted by additive noise.
