The ESPRIT and MUSIC algorithms using the covariance matrix

A computationally efficient algorithm for direction finding is described. The sample covariance matrix is averaged into d column vectors, where d is the known number of sources. These column vectors are used as a basis for the signal subspace. They can be used directly for the two subspace estimates in the ESPRIT algorithm or they can be used to construct a projection matrix for use with the MUSIC algorithm. For low signal-noise-ratio conditions, a subtraction process is used to remove the diagonal noise terms from the covariance matrix and as a result a shorter search vector is used in the MUSIC algorithm