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

Abstract

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.

Two-dimensional DOA estimation algorithm based on unitary ESPRIT under parallel nested arrays

“…This is because the large spacing of sparse arrays increases the effective aperture of the array, thereby improving the resolution of far-field signals, while the small spacing of dense arrays improves the resolution of near-field signals and sensitivity to low angle resolution signals. This combination not only improves the spatial resolution of the array, but also enhances its ability to capture multi-dimensional signal features [1] . In order to gain a deeper understanding of the performance of different array structures in practical applications, Figure 2 provides an intuitive comparison.…”