An extension of the MUSIC algorithm to broadband scenarios using polynomial eigenvalue decomposition

The multiple signal classification (MUSIC) algorithm for direction of arrival estimation is defined for narrowband scenarios. In this paper, a generalisation to the broadband case is presented, based on a description of broadband systems by polynomial space-time covariance matrices. A polynomial eigenvalue decomposition is used to determine the noiseonly subspace of the this matrix, which can be scanned by appropriately defined broadband steering vectors. Two broadband MUSIC algorithm versions are presented, which resolve either angle of arrival alone or in combination with the frequency range over which sources are active. Initial results for these approaches are presented and demonstrate a significant benefit over independent frequency bin processing using narrowband MUSIC.