  In this paper we present a new coherence-based performance guarantee for the
Orthogonal Matching Pursuit (OMP) algorithm. A lower bound for the probability
of correctly identifying the support of a sparse signal with additive white
Gaussian noise is derived. Compared to previous work, the new bound takes into
account the signal parameters such as dynamic range, noise variance, and
sparsity. Numerical simulations show significant improvements over previous
work and a closer match to empirically obtained results of the OMP algorithm.
