General direction-of-arrival estimation: a signal subspace approach

A high-resolution algorithm is presented for resolving multiple incoherent and coherent plane waves that are incident on an array of sensors. The incident sources can be a mixture of narrowband and broadband sources, and, the geometry of the array is unrestricted. The algorithm makes use of a fundamental property possessed by those eigenvectors of the array spectral density matrix that are associated with eigenvalues that are larger than the sensor noise level. Specifically, it is shown that these eigenvectors can each be represented as linear combinations of the steering vectors identifying the incident plane waves. This property is then used to solve the important special cases of incoherent sources incident on a general array and coherent sources incident on an equispaced linear array. Simulation results are presented to illustrate the high-resolution performance achieved with this approach relative to that obtained with MUSIC and spatial smoothed MUSIC in which the coherent-signal-subspace focusing method is used