Enhanced Two-Dimensional Direction of Arrival Estimation via Extended Connection Matrix

In this paper, we present a new methodology for performing 2D Direction of Arrival (DOA) estimation utilizing two-parallel coprime arrays. We first vectorize all the augmented auto-covariance and cross-covariance matrices to obtain an extended virtual difference coarray. Then, we drive all the augmented covariance matrices using the spatial smoothing outputs of the difference coarrays. Secondly, we construct an augmented connection matrix that incorporates complete augmented autocorrelation and cross-correlation information. Subsequently, the auto-paired DOA estimates are calculated using the eigenvalues and eigenvectors derived from the augmented connection matrix. Therefore, we can convert the 2D DOA estimation problem into two 1D estimation problems. Unlike the traditional DOA methods, our algorithm leverages the difference coarray to increase the array aperture. Additionally, our numerical evaluation validates the superiority of the proposed method compared to the state-of-the-art techniques.