A fast minimization technique for subspace fitting with arbitrary array manifolds

A new technique for minimization of a multidimensional subspace fitting criterion is proposed. An approximation is made to the exact criterion function, giving an explicit least squares solution for location parameters. Ideas from alternating projections are employed for initialization. The new technique gives global convergence with a high probability, has a low computational cost, is applicable to general array manifolds, and provides simple solutions for many problems with intricate parameterization.