Efficient estimation of the signal subspace without eigendecomposition

A method of obtaining estimates of a set of basis vectors spanning the signal subspace without eigendecomposition is described. Each basis vector can be determined as the solution to a linear least-squares prediction problem, thereby offering a reduction in computation of one order of magnitude compared with eigendecomposition-based methods. Experiments suggest that the proposed method has performance equal to that of MUSIC.<
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