FAST ALGORITHM FOR MINIMUM-NORM DIRECTION-OF-ARRIVAL ESTIMATION

The original minimum-norm direction-of-arrival estimator, proposed by Kumaresan and Tufts, employs the noise-subspace projection matrix, cal culated by the eigendecomposition of spatial covariance matrix. In thi s paper we propose a novel noneigenvector fast algorithm, which calcul ates the required minimum-norm function using the special power basis instead of eigenvector basis. Proposed algorithm provides a substantia l saving as compared with computational loads of eigendecomposition-ba sed minimum-norm algorithm in cases when the number of multiple source s is much lower than the number of array sensors. Some computer simula tion results, verifying the high performance and accuracy of the propo sed algorithm, are presented.