This paper reviews and compares three different linear algebraic signal subspace techniques for angle of arrival estimation. These include a polynomial matrix approach to multiple signal classification (MUSIC), a parameterised spatial covariance matrix approach, and an auto-focussing based version of coherent signal subspace estimation applied to MUSIC. These approaches are expressed in the framework of polynomial space-time covariance matrices and their polynomial eigenvalue decomposition, thus highlighting their commonalities and differences. Simulation results comparing the accuracy of these broadband angle of arrival estimation methods are presented.
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