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In this paper, we consider orthogonal matching pursuit (OMP) algorithm formultiple measurement vectors (MMV) problem. The robustness of OMPMMV is studiedunder general perturbations---when the measurement vectors as well as thesensing matrix are incorporated with additive noise. The main result shows thatalthough exact recovery of the sparse solutions is unrealistic in noisyscenario, recovery of the support set of the solutions is guaranteed undersuitable conditions. Specifically, a sufficient condition is derived thatguarantees exact recovery of the sparse solutions in noiseless scenario.

Performance of Orthogonal Matching Pursuit for Multiple Measurement Vectors