  In this paper, we consider orthogonal matching pursuit (OMP) algorithm for
multiple measurement vectors (MMV) problem. The robustness of OMPMMV is studied
under general perturbations---when the measurement vectors as well as the
sensing matrix are incorporated with additive noise. The main result shows that
although exact recovery of the sparse solutions is unrealistic in noisy
scenario, recovery of the support set of the solutions is guaranteed under
suitable conditions. Specifically, a sufficient condition is derived that
guarantees exact recovery of the sparse solutions in noiseless scenario.
