  Orthogonal matching pursuit (OMP) is a greedy algorithm widely used for the
recovery of sparse signals from compressed measurements. In this paper, we
analyze the number of iterations required for the OMP algorithm to perform
exact recovery of sparse signals. Our analysis shows that OMP can accurately
recover all $K$-sparse signals within $\lceil 2.8 K \rceil$ iterations when the
measurement matrix satisfies a restricted isometry property (RIP). Our result
improves upon the recent result of Zhang and also bridges the gap between
Zhang's result and the fundamental limit of OMP at which exact recovery of
$K$-sparse signals cannot be uniformly guaranteed.
