Before revision:  We prove theoretically that MISTR correctly recovers most signals distributed as a Gaussian point process  as long as sparsity is at most O \left( N ^{ D(}\right)  1/2 - \delta)}\left( \right) .
After revision:  We prove theoretically that MISTR correctly recovers most signals distributed as a Gaussian point process as long as sparsity is at most O \left( N ^{ D(}\right) 1/2 - \delta)}\left( \right) for \theta < 1/4 that obviates the need for MISTR to explicitly handle noisy autocorrelation data.