Off-grid direction-of-arrival estimation using second-order Taylor approximation

The problem of off-grid direction-of-arrival (DOA) estimation is investigated. We develop a grid-based method to jointly estimate the closest spatial frequency (the sine DOA) grids, and gaps between estimated grids corresponding frequencies. By using second-order Taylor approximation, data model under framework joint-sparse representation formulated. point out an important property signals interest in model, namely proportionality relationship, which empirically demonstrated be useful sense that it increases probability mixing matrix satisfying block restricted isometry property. Simulation examples demonstrate effectiveness superiority proposed against several state-of-the-art approaches.