Minimum-Norm Method without Eigendecomposition

The minimum-norm method (MNM) for high-resolution angles-of-arrival (AOA) estimation relies on special-purpose hardware or software for obtaining the signal and noise subspace eigenvectors of autocorrelation (AC) matrices. It is shown that the DFT of the AC matrix (DFT-of-AC) essentially performs an equivalent task of separating the signal and noise subspaces. Furthermore, when the signal-subspace part of the DFT-of-AC vectors are used in MNM, almost identical high-resolution AOA estimates are produced.