Gridless DOA Estimation and Root-MUSIC for Non-Uniform Linear Arrays

The problem of gridless direction arrival (DOA) estimation is addressed in the non-uniform array (NUA) case. Traditionally, DOA and root-MUSIC are only applicable for measurements from a uniform linear (ULA). This because sample covariance matrix ULA has Toeplitz structure, both algorithms based on Vandermonde decomposition matrix. breaks into its harmonic components, which DOAs estimated. First, we present `irregular' irregular (IVD), generalizes to apply more general set matrices. It shown that IVD related MUSIC algorithms. Next, generalized NUA case using IVD. resulting non-convex optimization solved alternating projections (AP). A numerical analysis performed AP solution shows generalization NUAs similar performance traditional DOA.