High-accuracy DOA estimation via parallel sparse nested array with extended aperture and reduced mutual coupling

This letter proposes a novel parallel sparse nested array and then provides a matrix reconstruction-based method with three steps, to enhance the performance of direction of arrival (DOA) estimation in practice. The spacings between the closest antennas along x- and y-axes, are coprime and much greater than half-wavelength in the proposed array, which contributes to efficiently eliminate the mutual coupling and achieve larger aperture with limited physical antennas. By using the oblique projection operator with iteration, the proposed method can employ all items of covariance matrix of the received data to construct a virtual covariance matrix with increased degrees of freedom, for effectively improving angle estimation performance. Then the unique and high-accuracy DOA estimation is obtained via the coprime-ness. The simulation results show the superiority of the proposed array and method for DOA estimation in the presence of mutual coupling and limited antennas. This letter presents a novel parallel sparse nested array and then proposes a matrix reconstruction-based method with three steps, to achieve better performance of direction of arrival (DOA) estimation. The spacings between the closest antennas along different axes, are coprime and much greater than half-wavelength in the proposed array, which contributes to effectively reduce the mutual coupling and enlarge the aperture with limited physical antennas. The proposed method can employ all items of covariance matrix of the received data to construct the virtual matrix with increased degrees of freedom, for efficiently enhancing angle estimation performance, and then obtain unique and high-accuracy DOA estimation by using the coprime-ness.image