On efficient gridless methods for 2-D DOA estimation with uniform and sparse L-shaped arrays

Abstract In recent years, some gridless methods have been developed for two-dimensional direction-of-arrival (DOA) estimation due to their superiority over on-grid or off-grid methods. However, the existing gridless methods treat every sparse planar array as a generalized planar array, regardless of some particular geometries of the arrays, e.g., the L-shaped arrays. Moreover, computational efficiency is another concern in designing gridless methods. In this paper, we propose two gridless methods for 2-D DOA estimation in the cases of both uniform and sparse L-shaped arrays by exploiting the cross-covariance matrix (CCM) of the array output. The first one is formulated based on the concept of atomic norm while the second one is developed by employing the covariance matching criterion. It is shown that the two methods become identical in uniform L-shaped array while exhibit different properties in sparse L-shaped array. Two computationally efficient algorithmic implementations are provided to make the proposed methods practically feasible. We finally carry out extensive experiments to verify the properties of our proposed methods.