A general approach to these problems is to use semidefinite optimization. The nearest correlation matrix estimation is one of the typical applications. The alternating projections might work well if the original matrix is nearly PSD, but it think it will be slow to converge otherwise. Also, the semidefinite optimization approach allows one to use different distance functions without chaning the algorithm.

Support for the is planned for the future in SAS/OR.