Efficient Two-Dimensional DOA Estimation for Coprime-Displaced Three Parallel Nested Arrays*

In this paper, we propose an efficient approach to estimate the directions-of-arrival (DOAs) of two dimensional (2-D) signals for coprime-displaced three parallel nested arrays (CPNAs), where the difference virtual coarray is exploited to realize the array aperture extension and degrees-of-freedom enhancement as a result. Specifically, the proposed approach is designed to fully make use of the auto-covariance matrix and cross-covariance matrix among the three subarrays, with which an augmented covariance matrix is formed. Then a reduced dimensional approach is proposed to decompose the 2-D problem as two one-dimensional (1-D) estimation problems via polynomial rooting with automatic angle pairing. The coprime displacement between the adjacent subarrays is adopted to enhance the resolution ability. Simulations are used to verify the improvement in estimation performance of the proposed approach.